• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.225-229
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• 2005

이류모형을 이용한 단기예측 레이더 강우자료와 관측 레이더자료의 비교를 통하여 얻어진 예측오차를 분석하였다. 임의 시점까지의 예측오차 장에 나타나는 확률분포 형태와 공간적 상관성을 분석하여 이들 특성을 반영하는 추후의 예측오차 장을 모의할 수 있었다. 모의된 예측오차 장과 합성된 단기예측 강우 장은 이류모형을 이용한 예측에 따른 불확실성 을 추계학적으로 반영한 예측강우를 제공한다.

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.311-329
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• 2005

Skewed t distributions have attracted significant attention in the last few years. In this paper, a generalization - referred to as the skewed generalized t distribution - with the pdf f(x) = 2g(x)G(${\lambda}x$) is introduced, where g(${\cdot}$) and G (${\cdot}$) are taken, respectively, to be the pdf and the cdf of the generalized t distribution due to McDonald and Newey (1984, 1988). Several particular cases of this distribution are identified and various representations for its moments derived. An application is provided to rainfall data from Orlando, Florida.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.352-362
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• 2017

This paper proposes an algorithm for automatically converting and displaying rainfall radar data on a 3D GIS platform. The weather information displayed like rainfall radar data is updated frequently and large-scale. Thus, in order to efficiently display the data, an algorithm to convert and output the data automatically, rather than manually, is required. In addition, since rainfall data is extracted from the space, the use of the display image fused with the 3D GIS data representing the space enhances the visibility of the user. To meet these requirements, this study developed the Auto Data Converter application that analyzes the raw data of the rainfall radar and convert them into a universal format. In addition, Unity 3D, which has good development accessibility, was used for dynamic 3D implementation of the converted rainfall radar data. The software applications developed in this study could automatically convert a large volume of rainfall data into a universal format in a short time and perform 3D modeling effectively according to the data conversion on the 3D platform. Furthermore, the rainfall radar data could be merged with other GIS data for effective visualization.

• Journal of Environmental Science International
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• v.18 no.9
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• pp.983-992
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• 2009

The purpose of the present study is to analyze pollutant runoff characteristics from non-point sources in Joman River basin. The present study contains analyzed results of rainfall and SS, BOD, COD, TN, TP runoff from Joman River basin. This study contains a sensitivity analysis of parameters that affect the simulation results of rainfall and pollutants runoff. Result of the sensitivity analysis shows that proportion of watershed and impervious areas is the most sensitive to peak discharge and total flowrate for rainfall runoff and that WASHPO is the most sensitive parameter for pollutants runoff. For parameter estimation and verification, flowrate and water quality is measured at the Kangdong Bridge in Haeban stream. A single rainfall event is use to perform parameter estimation and verification. Results of the present study show that total pollutant loads of Joman River basin is 11,600 ton of SS, 452 ton of BOD, 1,084 ton of COD, 515 ton of TN, and 49 ton of TP, respectively. In addition, it is found that contribution ratio of non point source and total source is 89% of SS, 63% of BOD, 61% of COD, 21% of TN, and 32% of TP, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.47-57
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• 2018

This study implemented the rainfall-runoff analysis of the Mekong River basin using the SWAT (Soil and Water Assessment Tool). The runoff analysis was simulated for 2000~2007, and 11 parameters were calibrated using the SUFI-2 (Sequential Uncertainty Fitting-version 2) algorithm of SWAT-CUP (Calibration and Uncertainty Program). As a result of analyzing optimal parameters and sensitivity analysis for 6 cases, the parameter ALPHA_BF was found to be the most sensitive. The reproducibility of the rainfall-runoff results decreased with increasing number of stations used for parameter calibration. The rainfall-runoff simulation results of Case 6 showed that the RMSE of Nong Khai and Kratie stations were 0.97 and 0.9, respectively, and the runoff patterns were relatively accurately simulated. The runoff patterns of Mukdahan and Khong Chaim stations were underestimated during the flood season from 2004 to 2005 but it was acceptable in terms of the overall runoff pattern. These results suggest that the combination of SWAT and SWAT-CUP models is applicable to very large watersheds such as the Mekong for rainfall-runoff simulation, but further studies are needed to reduce the range of modeling uncertainty.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.21-31
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• 2007

This study is aimed at the development of a runoff forecasting model by using the Fuzzy inference system and Neural Network model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting. The Neuro-Fuzzy (NF) model were used in this study. The NF model, recently received a great deal of attention, improve the existing Neural Networks by the aid of the Fuzzy theory applied to each node. The study area is the downstreams of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model respectively. The schematic diagram method and the statistical analysis are conducted to evaluate the feasibility of rainfall-runoff modeling. The model accuracy was rapidly decreased as the forecasting time became longer. The NF model can give accurate runoff forecasts up to 4 hours ahead in standard above the Determination coefficient $(R^2)$ 0.7. In the comparison of the runoff forecasting using the NF and TANK models, characteristics of peak runoff in the TANK model was higher than ones in the NF models, but peak values of hydrograph in the NF models were similar.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.1
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• pp.89-97
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• 2015

This study is to assess the effect of non-point source pollution discharge loads between tillage and no-tillage applications for upland crop areas using SWAT (Soil and Water Assessment Tool) watershed modeling. For Byulmi-cheon small rural catchment ($1.17km^2$) located in upstream of Gyeongan-cheon watershed, the rainfall, discharge and stream water quality have been monitored in the catchment outlet since 2011. The SWAT model was calibrated and validated in hourly basis using 19 rainfall events during 2011-2013. The average Nash-Sutcliffe model efficiency and $R^2$ (determination coefficient) for streamflow were 0.67 and 0.79 respectively. Using the 10 % surface runoff reduction from experiment results for no-tillage condition in field plots of 3 % and 8 % slopes under sesami cultivation, the soil saturated hydraulic conductivity for upland crop areas was adjusted from 0.001 mm/hr to 0.0025 mm/hr in average. Under the condition, the catchment sediment, T-N (total nitrogen, TN), and T-P (total phosphorus, TP) discharge loads were reduced by 6.9 %, 7.4 %, and 7.7 % respectively.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.15-27
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• 2018

Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.862-866
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• 2005

For urban watershed models, the ILLUDAS and SWMM are the popular rainfall-runoff models used in Korea. However, combined sewage systems in urban areas produced problems when a flood occured because of the surcharged precipitation amount which drained to the streams directly. Also, the lack of pipe line data and the difficulties of modeling yield inappropriate modeling results in urban runoff analysis. In addition, rainfall-runoff models in urban areas which use channel routing could have inaccurate and complicated processes. In this paper, the MIKE SWMM model has been applied for the stable runoff analysis of urban areas. Watershed and pipe line data were established by using past inundated records, DEM data, and the numerical pipe line data. For runoff modelings, the runoff block was adapted to a basin and the Extran block using dynamic equations was applied to the sewage system. After comparing to models that exist, it is concluded that the MIKE SWMM model produces reliable and consistence results without distorting the Parameters of the model.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.19-30
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• 2013

This study is to evaluate the use of dual-polarization radar data for storm runoff modeling in Namgang dam (2,293 $km^2$) watershed using KIMSTORM (Grid-based KIneMatic wave STOrm Runoff Model). The Bisl dual-polarization radar data for 3 typhoons (Khanun, Bolaven, Sanba) and 1 heavy rain event in 2012 were obtained from Han River Flood Control Office. Even the radar data were overall less than the ground data in areal average, the spatio-temporal pattern between the two data was good showing the coefficient of determination ($R^2$) and bias with 0.97 and 0.84 respectively. For the case of heavy rain, the radar data caught the rain passing through the ground stations. The KIMSTORM was set to $500{\times}500$ m resolution and a total of 21,372 cells (156 rows${\times}$137 columns) for the watershed. Using 28 ground rainfall data, the model was calibrated using discharge data at 5 stations with $R^2$, Nash and Sutcliffe Model Efficiency (ME) and Volume Conservation Index (VCI) with 0.85, 0.78 and 1.09 respectively. The calibration results by radar rainfall showed $R^2$, ME and VCI were 0.85, 0.79, and 1.04 respectively. The VCI by radar data was enhanced by 5 %.