• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.269-279
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• 2009

The design flood estimation in a large river basin has a lot of uncertainties in areal reduction factors, time-spatial rainfall distribution, and parameters of rainfall-runoff model. The use of historical concurrent rainfall events for estimating design flood would reduce the uncertainties. This study presents a procedure for estimating design floods using historical rainfall events and storage function model. The design rainfall and time-spatial distribution were determined through analyzing concurrent rainfall events, and the design floods were estimated using storage function model with a non-linear hydrology response. To evaluate the applicability of the procedure of this study, the estimated floods were compared to results of frequency analysis of flood data. Both floods gave very similar results. It shows the applicability of the procedure presented in this study for estimating design floods in practices.

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.469-482
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• 2014

This study developed a Bayesian spatial regional frequency analysis, which aimed to analyze spatial patterns of design rainfall by incorporating geographical information (e.g. latitude, longitude and altitude) and climate characteristics (e.g. annual maximum series) within a Bayesian framework. There are disadvantages to considering geographical characteristics and to increasing uncertainties associated with areal rainfall estimation on the existing regional frequency analysis. In this sense, this study estimated the parameters of Gumbel distribution which is a function of geographical and climate characteristics, and the estimated parameters were spatially interpolated to derive design rainfall over the entire Han-river watershed. The proposed Bayesian spatial regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis, and even better performance in terms of quantifying uncertainty of design rainfall and considering geographical information as a predictor.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1191-1195
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• 2006

Now days, heavy storm occur to be continue. It is hard to use before frequency based on flood discharge for decision that design water pocket structure. We need to estimation of frequency based on flood discharge on the important basin likely city or basin that damage caused by flood recurrence. In this paper flood discharge calculated by Clark watershed method and SCS synthetic unit hydrograph method about upside during each minute of among time distribution method of rainfall, Huff method choosing Bocheong Stream basin that is representative basin of International Hydrologic Project (IHP) about time distribution of rainfall that exert big effect at flood discharge estimate to research target basin because of and the result is as following. Relation between probability flood discharge that is calculated through frequency analysis about flood discharge data and rainfall - runoff that is calculated through outward flow model was assumed about $48.1{\sim}95.9%$ in the case of $55.8{\sim}104.0%$, SCS synthetic unit hydrograph method in case of Clark watershed method, and Clark watershed method has big value overly in case of than SCS synthetic unit hydrograph method in case of basin that see, but branch of except appeared little more similarly with frequency flood discharge that calculate using survey data. In the case of Critical duration, could know that change is big area of basin is decrescent. When decide time distribution type of rainfall, apply upside during most Huff 1-ST because heavy rain phenomenon of upsides appears by the most things during result 1-ST about observation recording of target area about Huff method to be method to use most in business, but maximum value of peak flood discharge appeared on Huff 3-RD too in the case of upside, SCS synthetic unit hydrograph method during Huff 3-RD incidental of this research and case of Clark watershed method. That is, in the case of Huff method, latitude is decide that it is decision method of reasonable design floods that calculate applying during all $1-ST{\sim}4-TH$.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.817-830
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• 2015

This study performed prediction of extreme rainfall uncertainty and its frequency analysis based on climate change scenarios by Coupled Model Intercomparison Project Phase 5 (CMIP5) for the selected nine-General Circulation Models (GCMs) in the near future (2011-2040) over the Korean Peninsula (KP). We analysed uncertainty of scenarios by multiple model ensemble (MME) technique using non-parametric quantile mapping method and bias correction method in the basin scale of the KP. During the near future, the extreme rainfall shows a significant gradually increasing tendency with the annual variability and uncertainty of extreme ainfall in the RCP4.5, and RCP8.5 scenarios. In addition to the probability rainfall frequency (such as 50 and 100-year return periods) has increased by 4.2% to 10.9% during the near future in 2040. Therefore, in the longer-term water resources master plan, based on the various climate change scenarios (such as CMIP5 GCMs) and its uncertainty can be considered for utilizing of the support tool for decision-makers in water-related disasters management.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.319-323
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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. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the Generalized extreme value distribution among apt]lied distributions. regional and at-site parameters of the Generalized extreme value distribution were estimated by the method of 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.

• 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.

• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.879-892
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• 2003

This study has performed the regionalization of point rainfall which has the hydrological homogeneity for regional frequency analysis of the rainfall. For the study, the recorded rainfall data were collected from 60 rainfall gauge stations distributed all over country of the Korea Meteorological Administration, and 32 rainfall characteristic elements were analyzed from the collected data. Using the principal component analysis to be data reduction technique of the multivariate analysis and the cluster analysis to be grouping technique about many of rainfall characteristic elements of each station, the regionalization of point rainfall was accomplished rationally and efficiently. As the result, hydrological homogeneous regions of point rainfall were divided by 5 regions and 3 other regions, and rainfall characteristics of divided each region were analyzed and compared relatively using regional mean values of each rainfall element data.

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.11-18
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• 2016

It is very important to decide probability precipitation that is used as hydraulic structure design and target rainfall for urban disaster prevention. Especially, National Emergency Management Agency (NAMA) announced target rainfall from probability precipitation in korea on city and district level. It make use to performance evaluation of disaster prevention and planning of development for disasters prevention capacity target. In this study was calculated target rainfall that is duration 1~3 hour based unit of gu (borough) by point and regional frequency analysis using rainfall data of Surface Synoptic Stations (SSS) and Automatic Weather Stations (AWS). The result of this study can utilized as a reference to related business such as disaster capability assessment and achievement of prevention capacity target against disasters. And it also will be contribute to establishment of prevention capacity target against disasters.

• 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.41 no.3
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• pp.251-264
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• 2008

In this study, a nonhomogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrologic variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and flood in the watershed, and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase. Therefore, with the proposed approach, the non-homogeneous markov model can be used to estimate variables for the purpose of design of hydraulic structures and analyze uncertainties associated with rainfall input in the hydrologic models.