• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.3
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• pp.41-50
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• 1999

Derivatio of reasonable design floods was attempted by comparative analysis of design floods derived by Generalized Extreme Value(GEV) distribution using methods of L-moments and LH-moments for the annual maximum series at ten watersheds along Han, Nagdong. Geum, Yeongsan and Seomjin river systems, LH-coefficient of variation, LH-skewness and Lh-kurtosis were calcualted by KH-moment ration respectively. Paramenters were estimated by the Method of LH-Moments, Design floods obtained by Method of LH-Moments using different methods for plotting positionsi n GEV distribution and design floods were compared with those obtained using the Method of L-Moments by the Relative Mean Errors(RME) and Relative Absolute Errors(RAE). The results was found that design floods derived by the method of L-Moments and LH-Moments using Cunnane plotting position formula in the GEV distribution are much closer to those of the observed data in comparison with those obtained by methods of L-moments and LH-moments using the other formula for plotting positions from the viewpoint of Relative Mean Errors and Relative Absolute Errors. In viewpoint of the fact that hydrqulic structures including dams and levees are genrally using design floods with the return period of two hundred years or so, design floods derived by LH-Moments are seemed to be more reasonable than those of L-Moments in the GEV distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 1999.05a
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• pp.104-110
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• 1999

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.59-64
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• 2000

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1027-1031
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• 2004

2001년에 발생한 가뭄 심도를 기왕의 주요 가뭄과 비교평가하기 위하여 전국을 95개 소유역으로 구분하고 월 강우량 계열로부터 작성된 갈수우량계열을 이용하여 지역빈도해석을 실시하였다. L-모멘트법을 사용하여 강우지속기간별, 재현기간별 갈수우량을 산정하고 지속기간별 확률갈수우량도를 작성하였다. 또한, 연평균강우량과 가뭄의 발생지역을 비교하여 강우량이 적은 지역과 가뭄이 자주 발생하는 지역의 연관성을 검토하였다. 강우지속기간-재현기간-갈수우량 관계를 고려하여 2001년 가뭄의 심도와 지역적 범위를 최근에 발생한 '95 가뭄과 비교 평가하였다. 본 연구를 통하여 2001년 가뭄의 특성과 용수공급을 위한 적정 방안을 제안하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1538-1542
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• 2007

확률강우량은 일반적으로 년최대 강우량자료를 바탕으로 빈도해석을 실시하여 산정하며, 국내에서는 주로 매시각별로 관측된 자료를 이용하여 지속기간 1시간에서 24시간 사이에 대하여 산정하고 있다. 그러나 도달시간이 매우 단시간인 도시 유역의 확률강우량 산정을 위해서는 지속기간 15분 혹은 지속기간 30분과 같은 짧은 지속기간에 대한 확률강우량의 추정이 필요하며, 이와는 반대로 지속기간 24시간 이상의 장기간에 대한 확률강우량의 추정이 필요한 경우도 있다. 본 연구에서는 이와 같이 관측되지 않은 지속기간에 대한 확률강 우량을 산정하기 위한 방법으로써 강우자료의 지속기간별로 일정한 스케일이 유지된다는 스케일링 성질(Scaling Invariance Property)을 적용하여 확률강우량을 산정하였다. 이를 위해 대상지역의 지속기간별 년최대 강우량자료를 구축한 뒤 L-모멘트법으로 산정된 매개변수와 스케일링 성질을 이용하여 확률강우량을 산정한 후 이를 기존의 빈도해석 결과에 의한 확률강우량과 비교하여 적용성을 판단하였다.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.364-364
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• 2004

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.59-64
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• 2000

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.259-267
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• 2009

Generalized Extreme Value (GEV) distribution is recommended for flood frequency and extreme rainfall distribution in many country. L-moment method is the most common estimation procedure for the GEV distribution. In this study, the relationships between the cross-site correlations between extreme events and the cross-correlation of estimators of L-moment ratios (L-moment Coefficient of Variation (L-CV) and L-moment Coefficient of Skewness (L-CS)) for data generated from GEV distribution were derived by Monte Carlo simulation. Those relationships were fit to the simple power function. In this Monte Carlo simulation, GEV+ distribution were employed wherein unrealistic negative values were excluded. The simple power models provide accurate description of the relationships between cross-correlation of data and cross-correlation of L-moment ratios. Estimated parameters and accuracies of the power functions were reported for different GEV distribution parameters combinations. Moreover, this study provided a description about regional regression approach using Generalized Least Square (GLS) regression method which require the cross-site correlation among L-moment estimators. The relationships derived in this study allow regional GLS regression analyses of both L-CV and L-CS estimators that correctly incorporate the cross-correlation among GEV L-moment estimators.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.4
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• pp.25-29
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• 1999

This study was conducted to derive optimal design floods by Gerneralized Extreme Value(GEV) and Weibull-3 distributions for the annual maximum series at ten watersheds along Han,Nagdong, Geum, Yeongsan and Seomjin reiver systems. Adequency for the analysis of flood data used in this study was established by the tests of Independence. Homogeneity , detection of Outlines, L-moments. Design flood sobtaine dby /methods of Moments and L-Moments using different methods for plotting positions in BEV and Weibull-3 distributions were compared by the Relative Mean Errors(RME) and Root MEan Square Errors(RMSE). The result wa found that design floods derived by the L-moments using the other formulas for plotting positions from the viewpoint of Relative Mean Errors and Root Mean Square Errors.