• Title/Summary/Keyword: 확률가중모멘트

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The Extreme Value Analysis of Deepwater Design Wave Height and Wind Velocity off the Southwest Coast (남서 해역 심해 설계 파고 및 풍속의 극치분석)

  • Kim, Kamg-Min;Lee, Joong-Woo;Lee, Hun;Yang, Sang-Yong;Jeong, Young-Hwan
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.29 no.1
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    • pp.245-251
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    • 2005
  • When we design coastal and harbol facilities deepwater design wave and wind speed are the important design parameters. Especially, the analysis of these informations is a vital step for the point of disaster prevention. In this study, we made and an extreme value analysis using a series of deep water significant wave data arranged in the 16 direction and supplied by KORDI real-time wave information system ,and the wind data gained from Wan-Do whether Station 1978-2003. The probability distributions considered in this characteristic analysis were the Weibull, the Gumbel, the Log-Pearson Type III, the Normal, the Lognormal, and the Gamma distribution. The parameter for each distribution was estimated by three methods, i.e. the method of moments, the maximum likelihood, and the method of probability weight moments. Furthermore, probability distributions for the extreme data had been selected by using Chi-square and Kolmogorov-Smirnov test within significant level of 5%, i,e. 95% reliance level. From this study we found that Gumbel distribution is the most proper model for the deep water design wave height off the southwest coast of Korea. However the result shows that the proper distribution made for the selected site is varied in each extreme data set.

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Characteristics on the Extreme Value Distributions of Deepwater Design ave Heights off the Korean Coast (한국 연안 심해 설계파고의 극치분포 특성)

  • Shin Taek Jeong;Jeong Dae Kim;Cho Hong Yeon
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.16 no.3
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    • pp.130-141
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    • 2004
  • For a coastal or harbor structure design, one of the most important environmental factors is the appropriate design wave condition. Especially, the information of deepwater wave height distribution is essential for reliability design. In this paper, a set of deep water wave data obtained from KORDI(2003) were analyzed for extreme wave heights. These wave data at 67 stations off the Korean coast from 1979 to 1998 were arranged in the 16 directions. The probability distributions considered in this research were the Weibull, the Gumbel, the Log-pearson Type-III, and Lognormal distribution. For each of these distributions, three parameter estimation methods, i.e. the method of moments, maximum likelihood and probability weighted moments, were applied. Chi-square and Kolmogorov-Smirnov goodness-of-fit tests were performed, and the assumed distribution was accepted at the confidence level 95%. Gumbel distribution which best fits to the 67 station was selected as the most probable parent distribution, and optimally estimated parameters and 50 year design wave heights were presented.

Estimation of Design Rainfall by the Regional Frequency Analysis using Higher Probability Weighted Moments and GIS Techniques (III) - On the Method of LH-moments and GIS Techniques - (고차확률가중모멘트법에 의한 지역화빈도분석과 GIS기법에 의한 설계강우량 추정 (III) - LH-모멘트법과 GIS 기법을 중심으로 -)

  • 이순혁;박종화;류경식;지호근;신용희
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.5
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    • pp.41-53
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    • 2002
  • 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. According to the regions and consecutive durations, optimal design rainfalls were derived by the regional frequency analysis for L-moment in the second report of this project. Using the LH-moment ratios and Kolmogorov-Smirnov test, the optimal regional probability distribution was identified to be the Generalized extreme value (GEV) distribution among applied distributions. regional and at-site parameters of the GEV distribution were estimated by the linear combination of the higher probability weighted moments, LH-moment. Design rainfall using LH-moments following the consecutive duration were derived by the regional and at-site analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design rainfall were computed and compared in the regional and at-site frequency analysis. Consequently, it was shown that the regional analysis can substantially more reduce the RRMSE, RBIAS and RR in RRMSE than at-site analysis in the prediction of design rainfall. Relative efficiency (RE) for an optimal order of L-moments was also computed by the methods of L, L1, L2, L3 and L4-moments for GEV distribution. It was found that the method of L-moments is more effective than the others for getting optimal design rainfall according to the regions and consecutive durations in the regional frequency analysis. Diagrams for the design rainfall derived by the regional frequency analysis using L-moments were drawn according to the regions and consecutive durations by GIS techniques.

Estimation of Design Rainfall by the Regional Frequency Analysis using Higher Probability Weighted Moments and GIS Techniques (고차확률가중모멘트법에 의한 지역화빈도분석과 GIS기법에 의한 설계강우량 추정)

  • Lee, Soon-Hyuk;Park, Jong-Hwa;Ryoo, Kyong-Sik;Jee, Ho-Keun;Shin, Yong-Hee
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2002.10a
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    • pp.237-240
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    • 2002
  • Design rainfall using LH-moments following the consecutive duration were derived by the regional and at-site analysis using the observed and simulated data resulted from Monte Carlo techniques. RRMSE, RBIAS and RR in RRMSE for the design rainfall were computed and compared in the regional and at-site frequency analysis. Consequently, it was shown that the regional analysis can substantially more reduce the RRMSE, RBIAS and RR in RRMSE than at-site analysis in the prediction of design rainfall. RE for an optimal order of L-moments was also computed by the methods of L, L1, L2, L3 and L4-moments for GEV distribution. It was found that the method of L-moments is more effective than the others for getting optimal design rainfall according to the regions and consecutive durations in the regional frequency analysis. Diagrams for the design rainfall derived by the regional frequency analysis using L-moments were drawn according to the regions and consecutive durations by GIS techniques.

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A Study on Statistical Characteristics for Extreme Rainfall based on CMIP6 SSP scenario - Focused on Busan Metropolitan City (CMIP6 SSP 시나리오 극한 강우량의 통계적 특성 연구 - 부산광역시를 중심으로)

  • Kim, Sunghun;Kim, Heechul;Kim, Gyobeom;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.410-410
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    • 2022
  • 기후변화에 관한 정부간 협의체(Intergovernmental Panel on Climate Change, IPCC)에서는 지난해부터 제6차 평가보고서(Sixth Assessment Report, AR6)를 준비하고 있으며, 최근 Working Group II에서 수행한 기후변화 영향, 적응 및 취약성(Impacts, Adaptation and Vulnerability) 보고서를 공개하였다. 보고서는 기존의 Representative Concentration Pathway (RCP) 시나리오에 사회경제적 조건을 추가로 고려한 Shared Socioeconomic Pathway (SSP) 시나리오를 제시하였고, 세계기후연구프로그램(World Climate Research Programme, WCRP)의 Coupled Model Intercomparison Project (CMIP)에서 제공하는 6단계(Phase 6) 미래 전망 자료를 적용하였다. 본 연구에서는 기후변화로 인한 미래 극한 강우량의 통계적 특성을 파악하기 위하여 CMIP6에서 제공하는 General Circulation Models (GCMs) 기반 미래 강우자료를 수집하여 부산광역시를 중심으로 분석하였다. 4개의 SSP (SSP126, SSP245, SSP370, SSP585) 시나리오별로 10개 GCMs의 모의 결과를 사용하였다. Gumbel 분포형과 확률가중모멘트법을 이용하여 미래 극한 강우량을 산정하였고, 현재 모의기간(S0, 1983-2014) 대비 미래 전망기간(S1, 2015-2044; S2, 2041-2070; S3, 2071-2100)의 변화를 재현기간(return period, T)별로 분석하여 제시하였다.

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The Determination of Probability Distributions of Annual, Seasonal and Monthly Precipitation in Korea (우리나라의 연 강수량, 계절 강수량 및 월 강수량의 확률분포형 결정)

  • Kim, Dong-Yeob;Lee, Sang-Ho;Hong, Young-Joo;Lee, Eun-Jai;Im, Sang-Jun
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.12 no.2
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    • pp.83-94
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    • 2010
  • The objective of this study was to determine the best probability distributions of annual, seasonal and monthly precipitation in Korea. Data observed at 32 stations in Korea were analyzed using the L-moment ratio diagram and the average weighted distance (AWD) to identify the best probability distributions of each precipitation. The probability distribution was best represented by 3-parameter Weibull distribution (W3) for the annual precipitation, 3-parameter lognormal distribution (LN3) for spring and autumn seasons, and generalized extreme value distribution (GEV) for summer and winter seasons. The best probability distribution models for monthly precipitation were LN3 for January, W3 for February and July, 2-parameter Weibull distribution (W2) for March, generalized Pareto distribution (GPA) for April, September, October and November, GEV for May and June, and log-Pearson type III (LP3) for August and December. However, from the goodness-of-fit test for the best probability distributions of the best fit, GPA for April, September, October and November, and LN3 for January showed considerably high reject rates due to computational errors in estimation of the probability distribution parameters and relatively higher AWD values. Meanwhile, analyses using data from 55 stations including additional 23 stations indicated insignificant differences to those using original data. Further studies using more long-term data are needed to identify more optimal probability distributions for each precipitation.

Estimation of Design Rainfalls Considering BCM2 Simulation Results (BCM2 모의 결과를 반영한 목표연도 확률강우량 산정)

  • Lee, Chang Hwan;Kim, Tae-Woong;Kyoung, Minsoo;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3B
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    • pp.269-276
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    • 2010
  • Climatic disasters are globally soaring due to recent acceleration of global warming. Especially the occurrence frequency of heavy rainfalls is increasing since the rainfall intensity is increasing due to the change of rainfall pattern, This study proposed the non-stationary frequency analysis for estimating design rainfalls in a design target year, considering the change of rainfall pattern through the climatic change scenario. The annual rainfalls, which are regionally downscaled from the BCM2 (A2 scenario) and NCEP data using a K-NN method, were used to estimate the parameters of a probability distribution in a design target year, based on the relationship between annual mean rainfalls and distribution parameters. A Gumbel distribution with a probability weighted method was used in this study. Seoul rainfall data, which are the longest observations in Korea, were used to verified the proposed method. Then, rainfall data at 7 stations, which have statistical trends in observations in 2006, were used to estimate the design rainfalls in 2020. The results indicated that the regional annual rainfalls, which were estimated through the climate change scenario, significantly affect on the design rainfalls in future.

Assessment and Improvement of Snow Load Codes and Standards in Korea (한국의 적설하중 기준에 대한 평가 및 개선방안)

  • Yu, Insang;Kim, Hayong;Necesito, Imee V.;Jeong, Sangman
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.5
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    • pp.1421-1433
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    • 2014
  • In this study, appropriate probability distribution and parameter estimation method were selected to perform snowfall frequency analysis. Generalized Extreme Value (GEV) and Probability Weighted Moment Method (PWMM) appeared to be the best fit for snowfall frequency analysis in Korea. Snowfall frequency analysis applying GEV and PWMM were performed for 69 stations in Korea. Peak snowfall corresponding to recurrence intervals were estimated based on frequency analysis while snow loads were calculated using the estimated peak snowfall and specific weight of snow. Design snow load map was developed using 100-year recurrence interval snow load of 69 stations through Kriging of ArcGIS. The 2009 Korean Building Code and Commentary for design snow load was assessed by comparing the design snow loads which calculated in this study. As reflected in the results, most regions are required to increase the design snow loads. Thus, design snow loads and the map were developed from based on the results. The developed design snow load map is expected to be useful in the design of building structures against heavy snow loading throughout Korea most especially in ungaged areas.

Downscaling Technique of Monthly GCM Using Daily Precipitation Generator (일 강수발생모형을 이용한 월 단위 GCM의 축소기법에 관한 연구)

  • Kyoung, Min Soo;Lee, Jung Ki;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.5B
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    • pp.441-452
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    • 2009
  • This paper describes the evaluation technique for climate change effect on daily precipitation frequency using daily precipitation generator that can use outputs of the climate model offered by IPCC DDC. Seoul station of KMA was selected as a study site. This study developed daily precipitation generation model based on two-state markov chain model which have transition probability, scale parameter, and shape parameter of Gamma-2 distribution. Each parameters were estimated from regression analysis between mentioned parameters and monthly total precipitation. Then the regression equations were applied for computing 4 parameters equal to monthly total precipitation downscaled by K-NN to generate daily precipitation considering climate change. A2 scenario of the BCM2 model was projected based on 20c3m(20th Century climate) scenario and difference of daily rainfall frequency was added to the observed rainfall frequency. Gumbel distribution function was used as a probability density function and parameters were estimated using probability weighted moments method for frequency analysis. As a result, there is a small decrease in 2020s and rainfall frequencies of 2050s, 2080s are little bit increased.

Estimation of Design Rainfall by the Regional Frequency Analysis using Higher Probability Weighted Moments and GIS Techniques(I) (고차확률가중모멘트법에 의한 지역화빈도분석과 GIS기법에 의한 설계강우량 추정(I) -동질성의 지역구분 방법을 중심으로-)

  • 이순혁;박종화;류경식;지호근;전택기;신용희
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.4
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    • pp.57-68
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    • 2001
  • It is matter of common knowledge to give impetus to the water resources development to cope with increasing demand and supply for the water utilization project including agricultural living and industrial water owing to the economic and civilization development in recent years. Regional design rainfall is necessary or the design of the dam reservoir levee and drainage facilities for the development of various kinds of essential waters including agricultural water. For the estimation of the regional design rainfall classification of the climatologically an geographically homogeneous regions should be preceded preferentially This study was mainly conducted to derive the optimal regionalization of the precipitation data which can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Wulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analysis. Both K-means clustering and mean annual precipitation methods are used to identify homogeneous regions all over the regions. Nine and five homogeneous regions for the precipitation were classified by the K-means clustering and mean annual methods, respectively. Finally, Five homogeneous regions were established by the trial and error method with homogeneity test using statistics of $\chi$$^2$ distribution.

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