• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.1
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• pp.33-44
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• 2003

This study was conducted to estimate the design flood by the determination of best fitting order for LH-moments of the annual maximum series at fifteen watersheds. Using the LH-moment ratios and Kolmogorov-Smirnov test, the optimal regional probability distribution was identified to be the Generalized Extreme Value (GEV) in the first report of this project. Parameters of GEV distribution and flood flows of return period n years were derived by the methods of L, L1, L2, L3 and L4-moments. Frequency analysis of flood flow data generated by Monte Carlo simulation was performed by the methods of L, L1, L2, L3 and L4-moments using GEV distribution. Relative Root Mean Square Error. (RRMSE), Relative Bias (RBIAS) and Relative Efficiency (RE.) using methods of L, Ll , L2, L3 and L4-moments for GEV distribution were computed and compared with those resulting from Monte Carlo simulation. At almost all of the watersheds, the more the order of LH-moments and the return periods increased, the more RE became, while the less RRMSE and RBIAS became. The Absolute Relative Reduction (ARR) for the design flood was computed. The more the order of LH-moments increased, the less ARR of all applied watershed became It was confirmed that confidence efficiency of estimated design flood was increased as the order of LH-moments increased. Consequently, design floods for the appled watersheds were derived by the methods of L3 and L4-moments among LH-moments in view of high confidence efficiency.

• Journal of Korea Water Resources Association
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• v.34 no.2
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• pp.119-130
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• 2001

At-site and regional frequency analyses of annual maximum 1-, 2-, and 3-days rainfall in Han River basin was performed and compared based on the regional L-moments algorithm. To perform regional frequency analysis, Han River basin was subdivided into 3 sub-basins such as South Han River, North Han River, and downstream regions. For each sub-basin, the discordancy and homogeneity tests were performed. As the results of goodness of fit tests, lognormal model was selected as an appropriate probability distribution for both South Han River and downstream regions and gamma-3 model for North han River region. From Monte carlo simulation, RBIAS and RRMSE of the estimated quantiles from regional frequency analysis and at-site frequency analysis were calculated and compared each other. Regional frequency analysis shows less RRMSE of the estimated quantiles than at-sites frequency analysis in overall return periods. The differences of BRMSE between two approaches increase as the return period increases. As a result, it is shown that regional frequency analysis performs better than at-site analysis for annual maximum rainfall data in Han River basin.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.811-821
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• 2007

The intensity-duration-frequency (IDF) curves by Talbot, Sherman and Japanese type formulas are widely used in South Korea since the parameters are easily estimated. However, these IDF curves' accuracies are relatively worse than those of the IDF curves developed by Lee et al. (1993) and Heo et al. (1999), and different parameters for the given return periods should be computed. In this study, parameter estimation method for the IDF curve by Heo et al. (1999) is suggested using genetic algorithm (GA). Quantiles computed by at-site frequency analysis using the rainfall data of 22 rainfall gauges operated by Korea Meteorological Administration are employed to estimate the parameters of IDF curves and minimizing root mean squared error (RMSE) and relative RMSE (RRMSE) of observed and computed quantiles are used as objective functions of GA. The comparison of parameter estimation methods between the empirical regression analysis and the suggested method show that the IDF curve in which the parameters are estimated by GA using RRMSE as an objective function is superior to the IDF curves using RMSE.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.252-263
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• 2008

This study was conducted to derive the optimal regionalization of the precipitation data which can be classified on the basis of climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung 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 analyses. K-means clustering mettled is used to identify homogeneous regions all over the regions. Five homogeneous regions for the precipitation were classified by the K-means clustering. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the generalized extreme value (GEV) distribution among applied distributions. The 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 regions and consecutive durations were derived by the regional frequency analysis.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.233-236
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order for LH-moments of the annual maximum series at fifteen watersheds. Parameters of GEV distribution and flood flows of return period n years were derived by the methods of L, L1, L2, L3 and L4-moments. Frequency analysis of flood flow data generated by Monte Carlo simulation was performed by the methods of L, L1, L2, L3 and L4-moments using GEV distribution. Relative Root Mean Square Error (RRMSE), Relative Bias (RBIAS) and Relative Efficiency (RE) using methods of L, L1, L2, L3 and L4-moments for GEV distribution were computed and compared with those resulting from Monte Carlo simulation. At almost all of the watersheds, the more the order of LH-moments and the return periods increased, the more RE became, while the less RRMSE and RBIAS became. Consequently, design floods for the applied watersheds were derived by the methods of L3 and L4-moments among LH-moments in view of high confidence efficiency.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.4
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• pp.25-36
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• 2004

This study was conducted to derive the design rainfall by the consecutive duration using the at-site frequency analysis. Using the errors, K-S tests and LH-moment ratios, Log Pearson type 3 (LP3) and Generalized Extreme Value (GEV) distributions of Gamma and Non-Gamma Family, respectively were identified as the optimal probability distributions among applied distributions. Parameters of GEV and LP3 distributions were estimated by the method of L and LH-moments and the Indirect method of moments respectively. Design rainfalls following the consecutive duration were derived by at-site frequency analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE) and relative efficiency (RE) in RRMSE for the design rainfall derived by at-site analysis in the observed and simulated data were computed and compared. It has shown that at-site frequency analysis by GEV distribution using L-moments is confirmed as more reliable than that of GEV and LP3 distributions using LH-moments and Indirect method of moments in view of relative efficiency.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1072-1076
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• 2008

본 연구에서는 한강유역 109개 지점의 강우관측소에서 관측된 지속기간별 연최대강우량을 기본으로 각 지속기간별 L-모멘트값을 산정하고, 한강유역에 적합한 빈도해석기법을 정의하기 위하여 지역구분을 실시하였다. 지역구분을 위한 군집분석을 수행하기 위하여 각 지점별 기상학적 인자와 지형학적 인자를 변수로 사용하였다. 군집분석 기법인 Ward, 평균연결법, Fuzzy-c means, Two-Step방법을 이용하여 지역구분을 실시하였다. GIS를 이용하여 각 방법들을 이용하여 군집된 결과를 도시한 결과 Fuzzy-c means방법으로 구분된 지역구분이 적합한 것으로 나타났다. 또한 구분된 지역의 동질성 여부를 판단하고 적정 분포형을 선정하였으며 지점빈도해석 및 지역빈도해석을 통하여 빈도별 확률 수문량을 산정하였다. 산정된 결과의 정확도 알아보기 위해 모의발생을 시킨 후, 각 기법별로 산정된 상대 평균 제곱근 오차(Relative Root Mean Square Error, RRMSE)를 비교 분석한 결과 대체적으로 지수홍수법과 계층적 방법이 낮은 RRMSE를 나타냈다. 따라서 한강유역에서는 지수홍수법과 계층적 방법을 적용한 지역빈도해석이 적합한 것으로 판단된다.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.561-568
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• 2015

In this study we predict apartment prices per unit in Daegu-Gyeongbuk areas by spatial lag and spatial error models, both of which belong to so-called spatial regression model. A spatial weight matrix is constructed by k-nearest neighbours method and then the models for the apartment prices in March, 2012 are fitted using the weight matrix. The apartment prices in March, 2013 are predicted by the fitted spatial regression models and then performances of two spatial regression models are compared by RMSE (root mean squared error), RRMSE (root relative mean squared error), MAE (mean absolute error).

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.959-972
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• 2014

In this study, a space-time rainfall grid field generation model based on multifractal theory was verified using nine flood events in the upstream watershed of Chungju dam in South Korea. For this purpose, KMA radar rainfall data sets were analyzed for the space-time multifractal characteristics. Simulated rainfall fields that represent the multifractal characteristics of observed rainfall field were reproduced using the space-time rainfall grid field generation model with log-Poisson distribution and three-dimension wavelet function. Simulated rainfall fields were applied to the S-RAT model as input data and compared with both observed rainfall fields and low-resolution rainfall field runoff. Error analyses using RMSE, RRMSE, MAE, SS, NPE and PTE indicated that the peak discharge increases about 20.03% and the time to peak decreases about 0.81%.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.179-188
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• 2011

In this study, the regional factors in Gangwondo were used to analysis the relationship between point precipitation and areal precipitation. The most province area in Gangwondo is consist of mountainous terrain. At the east part of the Taebaek Mountains, the slope is very steep and the coastal plains don't exist. At the west part of the Taebaek Mountains, the slope is mild, there are many rivers, such as South Han-river and North Han-river, and the regions are very complex terrain. The data of 66 stations in Gangwondo and the PRISM (Parameter-elevation Regression on Indepedent Slope Model) were used to estimate the spatial distribution of precipitation. According to the topographic conditions, such as elevation and slope, and the regional conditions, such as Youngdong and Youngseo, the spatial distribution of precipitation is well shown. At the results of cross-validation, the RRBIAS and the RRMSE are under 0.1 and therefore the analysis of the PRISM are well conducted. Consequently the PRISM in this study is a appropriate method to estimate the spatial distribution of precipitation in Gangwondo.