• Korean Journal of Hydrosciences
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• v.4
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• pp.11-19
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• 1993

The peak flood discharge at a downstream station and the flood travel time between a pair of dams due to a specific flood release from the upper reservoir are computed using a hydraulic river channel routing method. The study covered the whole large reservoir system in the Han River, Korea. The computed flood discharges and the travel times between dams were correlated with the duration and the magnitude of flood release rate at the upstream reservoir, and hence a multiple regression model is proposed for each river reach between a pair of dams. The peak flood discharge at a downstream location can be converted to the peak flood stage by a rating curve. Hence, the proposed regression model could be used to forecast the peak flood stage at a downstream location and the flood travel time between dams using the information on the flood travel time, release rate and duration from the upper dam.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.452-460
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• 2010

This study carried out stability evaluation for design flood stage of vegetation models with river sites using 1D HEC-RAS and 2D RMA-2 numerical models. The vegetation models established in this study were divided into which channel reaches consist of urban, rural and mountain rivers with the social and cultural significance of the sites. Examination results from the numerical models showed a similar aspect with the design flood stage of these rivers before vegetation modeling. Also, no embankment overflow was shown from the urban river with additional vegetation density of 25%, although there were approximately 0.20m rising in the flood stage. In case of ural and mountain rivers, vegetation models showed scarce rising in flood stage.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.675-678
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• 2008

An abnormal storm by the typhoon of RUSA in 2002th year was broken out with tremendous flood demages and inundations on the basin of Chogangcheon located in the upper middle part of Guem river's upstream. This flood could not be engaged because it was so big that the stage engaging Songcheon station stuck to Songcheon bridge was destroyed by submerging. In this study the quantity of the flood was calculated by use of Manning's equation and suitable roughness coefficient was suggested.

• Journal of Korea Water Resources Association
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• v.38 no.2
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• pp.121-131
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• 2005

In this study, a flood routing model is used for analyzing change of flood stage induced by various factors. The results by using the past cross section measurement data showed the minimum error in case of accurate measurement of cross section as well as reasonable boundary condition of model. In analyzing the rise of flood stage of main stream considering Inflow magnitude of tributary, it showed that the larger the flow magnitude is, the smaller the variance of stage is. The results of analysis in the tidal effect at Wolgot are that the tidal effect influence the stage profile into upstream in case of normal discharge of main stream and tributary but doesn't influence it even with maximum flood tide in case of project flood. Finally, when the various hydraulic factors are considered in numerical analysis, more systematic and realistic flood forecast system is able to be performed.

• Water for future
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• v.25 no.3
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• pp.115-124
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• 1992

The peak flood discharge at a downstream station and the flood travel time between a pair of dams due to a specific flood release from the upper reservoir are computed using a hydraulic river channel routing method. The study covered the whole reservoir system in the Han River. The computed peak flood discharges and the travel times between dams were correlated with the duration and the magnitude of flood release rate at the upstream reservoir, and hence a multiple regression model is proposed for each river reach between a pair of dams. The peak flood discharge at a downstream location can be converted to the peak flood stage by rating curve. Hence, the proposed regression model could be used to forecast the peak flood stage at a downstream location and the flood travel time between dams using the information on the flood release rate and duration from the upper dam.

• Water for future
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• v.26 no.2
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• pp.59-65
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• 1993

In the present study the methods proposed by Fuller and Sangal were evaluated to estimate the peak flood discharge based on the mean daily discharges during a flood period. The total of 198 flood events observed at seven stage gauging stations in the Han River basin were analyzed. The result showed that the peak flood discharges estimated based on the mean daily flows have a relatively high correlation with the observed peak floods. Hence, a regionalized relation and method is proposed for a possible application to estimate the peak flood discharges at the stage gauging stations with no hourly flood stage data, but with the mean daily stages.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1B
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• pp.9-20
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• 2012

Recently to overcome limitations of conceptual, hydrological and physics based models for flood stage forecasting, multiple linear regression model as one of data-driven models have been widely adopted for forecasting flood streamflow(stage). The objectives of this study are to compare performance of different multiple linear regression models according to regression coefficient estimation methods and determine most effective multiple linear regression flood stage forecasting models. To do this, the time scale was determined through the autocorrelation analysis of input data and different flood stage forecasting models developed using regression coefficient estimation methods such as LS(least square), WLS(weighted least square), SPW(stepwise) was applied to flood events in Jungrang stream. To evaluate performance of established models, fours statistical indices were used, namely; Root mean square error(RMSE), Nash Sutcliffe efficiency coefficient (NSEC), mean absolute error (MAE), adjusted coefficient of determination($R^{*2}$). The results show that the flood stage forecasting model using SPW(stepwise) parameter estimation can carry out the river flood stage prediction better in comparison with others, and the flood stage forecasting model using LS(least square) parameter estimation is also found to be slightly better than the flood stage forecasting model using WLS(weighted least square) parameter estimation.

• Water Engineering Research
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• v.2 no.2
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• pp.113-121
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• 2001

The objective of this study is to develop a prediction mode for a flood forecasting system in the downstream of the Nakdong river basin. Ranging from the gauging station at Jindong to the Nakdong estuary barrage, the hydraulic flood routing model(DWOPER) based on the Saint Venant equation was calibrated by comparing the calculated river stage with the observed river stages using four different flood events recorded. The upstream boundary condition was specified by the measured river stage data at Jindong station and the downstream boundary condition was given according to the tide level data observed at he Nakdong estuary barrage. The lateral inflow from tributaries were estimated by the rainfall-runoff model. In the calibration process, the optimum roughness coefficients for proper functions of channel reach and discharge were determined by minimizing the sum of the differences between the observed and the computed stage. In addition, the forecasting lead time on the basis of each gauging station was determined by a numerical simulation technique. Also, we suggested a model structure for a real-time flood forecasting system and tested it on the basis of past flood events. The testing results of the developed system showed close agreement between the forecasted and observed stages. Therefore, it is expected that the flood forecasting system we developed can improve the accuracy of flood forecasting on the Nakdong river.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1427-1431
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• 2007

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.669-673
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• 2008

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.