• Wind and Structures
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• v.34 no.6
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• 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.

• 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.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.2
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• pp.120-127
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• 2012

Exploratory data analysis was carried out by using the long-term wave climate data in Sokcho coastal zone. The main features found in this study are as follows. The coefficient of variations on the wave height and period are about 0.11 and 0.02, respectively. It also shows that the annual components of the wave height and period are dominant and their amplitudes are 0.24 m and 0.56 seconds, respectively. The amount of intra-annual variation range is about two times greater than that of the inter-annual variation range. The distribution shapes of the wave data are very similar to the log-normal and GEV(generalized extreme value) functions. However, the goodness-of-fit tests based on the KS test show as "rejected" for all suggested density functions. Then, the structure of the timeseries wave height data is roughly estimated as AR(3) model. Based on the wave duration results, it is clearly shown that the continuous and maximum duration is decreased as a power function shape and the total duration is exponentially decreased. Meanwhile, the environment of the Sokcho coastal zone is classified as a wave-dominated environment.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.13-24
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• 2007

This study is to derive the rainfall intensity formula based on the representative probability distribution using multivariate analysis in Korea. The annual maximum rainfall data at 57 stations having more than 30years long records were used for 12 durations(10min, 1, 2, 3, 4, 5, 6, 8, 10, 12, 18, 24hr). 50 rainfall characteristics elements are analyzed from the collected data. The widely used 14 probability distributions are applied to the basic data in hydrologic frequency analysis. The homogeneous tests(principal component and cluster analysis) are applied to find the rainfall homogeneity. The results of this study are as followings; (1) The homogeneous test shows that there is no appropriate representative distribution for the whole duration in Korea. But hydrological homogeneous regions of point rainfall could be divided by 5 regions. (2) The GEV distribution for zones I, III, IV, V and the Gumbel distribution for zone II are determined as the representative probability distribution. (3) Comparative analysis of the results shows that the probable rainfalls of representative zones are different from those of existing researches. (4) Rainfall intensity formulas are determined on the basis of the linearization technique for the probable rainfall.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.229-232
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.827-837
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• 2012

The estimation of the rainfall quantile is of great importance in designing hydrologic structures. Conventionally, the rainfall quantile is estimated by univariate frequency analysis with an appropriate probability distribution. There is a limitation in which duration of rainfall is restrictive. To overcome this limitation, bivariate frequency analysis by using 3 copula models is performed in this study. Annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables. Gumbel (GUM), generalized logistic (GLO) distributions are applied for rainfall depth and generalized extreme value (GEV), GUM, GLO distributions are applied for rainfall duration. Copula models used in this study are Frank, Joe, and Gumbel-Hougaard models. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula, and the method of probability weighted moments is used to estimate the parameters of marginal distributions. Rainfall quantile from this procedure is compared with various marginal distributions and copula models. As a result, in change of marginal distribution, distribution of duration does not significantly affect on rainfall quantile. There are slight differences depending on the distribution of rainfall depth. In the case which the marginal distribution of rainfall depth is GUM, there is more significantly increasing along the return period than GLO. Comparing with rainfall quantiles from each copula model, Joe and Gumbel-Hougaard models show similar trend while Frank model shows rapidly increasing trend with increment of return period.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.521-531
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• 2006

The formula was proposed through the examination of probability rainfall intensity formula used in Incheon based upon recent occurrences of heavy rain and extraordinary storms. Random-time maximum annual rainfalls were estimated for durations from ten minutes to twenty-four hours from the data by Korea Meteorological Administration. Eleven types of probability distribution are considered to estimate probable rainfall depths for different storm durations at Incheon city. Three goodness-of-fit tests including Chi-square, Kolmogorov-Smirmov and framer Von Misses were used to analyze the tendency of recent rainfall. Considering maximum rainfall occurred, General Extreme Value(GEV) distribution was chosen as the appropriate probability distribution. Five types of probability rainfall formulas including Talbot type, Sherman type, Japanese type, unified type I and unified type II are considered to determine the best type for rainfall intensity at Incheon. The formula was determined considering the time of concentration of sewer system and river at Incheon city. Unified type I was chosen for its accuracy and was proposed to represent rainfall intensity of Incheon district.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.439-450
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• 2016

For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.

• 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.