• Journal of Wetlands Research
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• v.17 no.3
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• pp.251-263
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• 2015

This study suggested a novel approach of estimating the optimal probability density function (OPDF) of the annual maximum rainfall time series (AMRT) combining the L-moment ratio diagram and the geographical information system. This study also reported several interesting geographical characteristics of the AMRT in Korea. To achieve this purpose, this study determined the OPDF of the AMRT with the duration of 1-, 3-, 6-, 12-, and 24-hours using the method of L-moment ratio diagram for each of the 67 rain gages in Korea. Then, a map with the Thiessen polygons of the 67 rain gages colored differently according the different type of the OPDF, was produced to analyze the spatial trend of the OPDF. In addition, this study produced the color maps which show the fitness of a given probability density function to represent the AMRT. The study found that (1) both L-skewness and L-kurtosis of the AMRT have clear geographical trends, which means that the extreme rainfall events are highly influenced by geography; (2) the impact of the altitude on these two rainfall statistics is greater for the mountaneous region than for the non-mountaneous region. In the mountaneous region, the areas with higher altitude are more likely to experience the less-frequent and strong rainfall events than the areas with lower altitude; (3) The most representative OPDFs of Korea except for the Southern edge are Generalized Extreme Value distribution and the Generalized Logistic distribution. The AMRT of southern edge of Korea was best represented by the Generalized Pareto distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.635-639
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• 2004

댐과 같은 구조물의 설계시 큰 강우량에 내한 분포함수의 적합성을 놀일 필요가 있다. 이에 대해 Wang (1997a and b)은 큰 설계량에 내한 적합성을 놀이기 위해 LH 모멘트와 고차 PWM(higher Probability Weighted Moments)방법을 제안하였다. 따라서 본 연구에서는 우리나라의 자 지역별로 대표적인 4개 지점의 일 강우량 자료를 사용하여 제안된 고차 PWM 방법의 적용성을 살펴보았다. 그 과정으로 가장 낮은 차수인 일반적인 PWM 방법과 더 높은 차수의 PWM 방법을 이용하여, GEV(Generalized Extreme Value) 분포와 Gumbel 분포에 대한 매개변수를 추정한 후 이 추정치를 확률지에 실측치와 함께 도시하여 결과를 비교하였다. 그리고 PPCC(Probability Plot Correlation Coefficient) 적합도 검정결과를 통해 추정된 매개변수의 적합성을 확인하였다.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.27-39
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• 2004

In the first part of this study, five homogeneous regions in view of topographical and geographically homogeneous aspects except Jeju and Ulreung islands in Korea were accomplished by K-means clustering method. A total of 57 rain gauges were used for the regional frequency analysis with minimum rainfall series for the consecutive durations. Generalized Extreme Value distribution was confirmed as an optimal one among applied distributions. Drought rainfalls following the return periods were estimated by at-site and regional frequency analysis using L-moments method. It was confirmed that the design drought rainfalls estimated by the regional frequency analysis were shown to be more appropriate than those by the at-site frequency analysis. In the second part of this study, LH-moment ratio diagram and the Kolmogorov-Smirnov test on the Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions were accomplished to get optimal probability distribution. Design drought rainfalls were estimated by both at-site and regional frequency analysis using LH-moments and GEV distribution, which was confirmed as an optimal one among applied distributions. Design rainfalls were estimated by at-site and regional frequency analysis using LH-moments, the observed and simulated data resulted from Monte Carlotechniques. Design drought rainfalls derived by regional frequency analysis using L1, L2, L3 and L4-moments (LH-moments) method have shown higher reliability than those of at-site frequency analysis in view of RRMSE (Relative Root-Mean-Square Error), RBIAS (Relative Bias) and RR (Relative Reduction) for the estimated design drought rainfalls. Relative efficiency were calculated for the judgment of relative merits and demerits for the design drought rainfalls derived by regional frequency analysis using L-moments and L1, L2, L3 and L4-moments applied in the first report and second report of this study, respectively. Consequently, design drought rainfalls derived by regional frequency analysis using L-moments were shown as more reliable than those using LH-moments. Finally, design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were derived by regional frequency analysis using L-moments, which was confirmed as a more reliable method through this study. Maps for the design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were accomplished by the method of inverse distance weight and Arc-View, which is one of GIS techniques.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.337-351
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• 2010

There is a growing dissatisfaction with use of conventional statistical methods for the prediction of extreme events. Conventional methodology for modeling extreme event consists of adopting an asymptotic model to describe stochastic variation. However asymptotically motivated models remain the centerpiece of our modeling strategy, since without such an asymptotic basis, models have no rational for extrapolation beyond the level of observed data. Also, this asymptotic models ignored or overestimate the uncertainty and finally decrease the reliability of uncertainty. Therefore this article provide the research example of the extreme rainfall event and the methodology to reduce the uncertainty. In this study, the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) and the MLE (Maximum Likelihood Estimation) methods using a quadratic approximation are applied to perform the at-site rainfall frequency analysis. Especially, the GEV distribution and Gumbel distribution which frequently used distribution in the fields of rainfall frequency distribution are used and compared. Also, the results of two distribution are analyzed and compared in the aspect of uncertainty.

• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.889-902
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• 2011

In this study, frequency analysis using drought index had implemented for the derivation of drought severity-duration-frequency (SDF) curves to enable quantitative evaluations of past historical droughts having been occurred in Korean Peninsular. Seoul, Daejeon, Daegu, Gwangju, and Busan weather stations were selected and precipitation data during 1974~2010 (37 years) was used for the calculation of Standardized Precipitation Index (SPI) and frequency analysis. Based on the results of goodness of fit test on the probability distribution, Generalized Extreme Value (GEV) was selected as most suitable probability distribution for the drought frequency analysis using SPI. This study can suggest return periods for historical major drought events by using newrly derived SDF curves for each stations. In case of 1994~1995 droughts which had focused on southern part of Korea. SDF curves of Gwangju weather station showed 50~100 years of return period and Busan station showed 100~200 years of return period. Besides, in case of 1988~1989 droughts, SDF of Seoul weather station were appeared as having return periods of 300 years.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1001-1012
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• 2016

It is well known that air pollutants exert a bad influence on human health. According to the United Nations Environment Program, 4.3 million people die from carbon monoxide and particulate matter annually from all over the world. Carbon monoxide is a toxic gas that is the most dangerous of the gas consisting of carbon and oxygen. In this paper, we used 1 hour, 6 hours, 12 hours, and 24 hours average carbon monoxide concentration data collected between 2004 and 2013 in Daegu Gyeongbuk area. Parameters of the generalized extreme value distribution were estimated by maximum likelihood estimation and L-moments estimation. An evalution of goodness of fitness also was performed. Since the number of samples were small, L-moment estimation turned out to be suitable for parameter estimation. We also calculated 5 year, 10 year, 20 year, and 40 year return level.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.122-122
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• 2011

수자원 분야에서 기후변화 관련 연구는 치수 측면 보다는 이수 측면에서 주로 이뤄지고 있다. 이는 홍수분석을 위한 시간 단위를 충족시켜주는 전지구 대기순환모형(Global Circulation Model: GCM)의 자료가 드물고, 시간 단위의 GCM 자료라 하더라도 극치값(extreme value) 표현에는 한계가 있기 때문이다. 이를 극복하기 위하여 과거 관측자료의 통계적 특성으로 극치자료의 편의(bias)를 보정하고 시간 단위로 분해하기도 한다. 하지만 이런 통계적 상세화(statistical downscaling)는 미래 기후는 과거자료와 통계적 차이가 유의하지 않음을 가정하고 있어, 미래 기후는 현재와 다를 것이라는 공감대에 는 적합하지 않다. 이와 같은 이유로 타당한 극치수문변수 결과를 얻기 위해서는 시간 단위의 고분해능(high resolution) GCM이나 지역기후모델(regional climate model)과 같은 고해상도의 미래 기후변화 자료가 필요하게 된다. 이에 국립기상연구소에서는 영국 기상청의 통합모델(UM)기반의 지역기후모델(HadGEM3)을 사용하여 50 km 및 12.5 km 격자 단위로 역학적 상세화(dynamic downscaling)를 수행하였다. 본 연구에서는 개발된 HadGEM3-RA 결과의 극치수문변수 검증을 위하여 한강유역의 관측 자료와 다양한 방법으로 비교하였다. 두 자료의 극치값을 GEV (Generalized Extreme Value) 분포에 적합(fitting)시켜 비초과확률별 극치사상과, 특정 임계값(threshold value) 이상의 극치사상 발생확률을 비교하였다. 검토 결과, HadGEM3-RA는 통계적 상세화로 구한 극치값 보다는 작았으나 기존의 지역 기후모델에 비하여 현실성 있는 극치값이 계산되었음을 확인하였다.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.4
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• pp.45-57
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• 1998

This study was conducted to derive optimal design floods by Generalized Extreme Value (GEV) distribution for the annual maximum series at ten watersheds along Han, Nagdong, Geum, Yeongsan and Seomjin river systems. Adequacy for the analysis of flood data used in this study was established by the tests of Independence, Homogeneity, detection of Outliers. L-coefficient of variation, L-skewness and L-kurtosis were calculated by L-moment ratio respectively. Parameters were estimated by the Methods of Moments and L-Moments. Design floods obtained by Methods of Moments and L-Moments using different methods for plotting positions in GEV distribution were compared by the Relative Mean Errors(RME) and Relative Absolute Errors(RAE). The results were analyzed and summarized as follows. 1. Adequacy for the analysis of flood data was acknowledged by the tests of Independence, Homogeneity and detection of Outliers. 2. GEV distribution used in this study was found to be more suitable one than Pearson type 3 distribution by the goodness of fit test using Kolmogorov-Smirnov test and L-Moment ratios diagram in the applied watersheds. 3. Parameters for GEV distribution were estimated using Methods of Moments and L-Moments. 4. Design floods were calculated by Methods of Moments and L-Moments in GEV distribution. 5. It was found that design floods derived by the method of L-Moments using Weibull plotting position formula in GEV distribution are much closer to those of the observed data in comparison with those obtained by method of moments using different formulas for plotting positions from the viewpoint of Relative Mean Errors and Relative Absolute Errors.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.5
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• pp.70-82
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• 2001

This study was conducted to derive the regional design rainfall by the regional frequency analysis based on the regionalization of the precipitation suggested by the first report of this project. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among applied distributions. Regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error(RRMSE), relative bias(RBIAS) and relative reduction(RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the legions and consecutive durations were derived by the regional frequency analysis.

• Wind and Structures
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• v.38 no.4
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• pp.309-323
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• 2024

The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.