• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.194-194
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• 2017

Flooding is one of the most serious and frequently occurred natural disaster at many regions around the world. Especially, under the climate change impact, it is more and more increasingly trend. To reduce the flood damage, flood forecast and its accuracy analysis are required. This study is conducted to analyze the accuracy of the real-time flood forecasting of a coupled meteo-hydrological model for the Han River basin, South Korea. The LDAPS (Local Data Assimilation and Prediction System) products with the spatial resolution of 1.5km and lead time of 36 hours are extracted and used as inputs for the SURR (Sejong University Rainfall-Runoff) model. Three statistical criteria consisting of CC (Corelation Coefficient), RMSE (Root Mean Square Error) and ME (Model Efficiency) are used to evaluate the performance of this couple. The results are expected that the accuracy of the flood forecasting reduces following the increase of lead time corresponding to the accuracy reduction of LDAPS rainfall. Further study is planed to improve the accuracy of the real-time flood forecasting.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.157-164
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• 2008

A modeling and visualization system of flood inundation in natural river, FloodViz, has been developed. Unsteady river flow and flood inundation are calculated by FLDWAV model. FLDWAV model and HEC-RAS model have been applied to a flood event at the same time to check model reliability. Simulation results of the two models showed good agreements. Flood propagation and inundation process can be analyzed accurately and easily by using visualization function of the FloodViz. Even though FloodViz users don't know well about both hydraulics and hydrology, they can understand flood inundation phenomena easily. This system can be used as a useful tool in forecasting flood inundation and observing the simulation results. Countermeasures for natural disaster prevention due to flood inundation can be established rapidly by using the FloodViz.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.146-146
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• 2022

A flash flood is one of the most hazardous natural events caused by heavy rainfall in a short period of time in mountainous areas with steep slopes. Early warning of flash flood is vital to minimize damage, but challenges remain in the enhancing accuracy and reliability of flash flood forecasts. The forecasters can easily determine whether flash flood is occurred using the flash flood guidance (FFG) comparing to rainfall volume of the same duration. In terms of this, the hydrological model that can consider the basin characteristics in real time can increase the accuracy of flash flood forecasting. Also, the predicted radar rainfall has a strength for short-lead time can be useful for flash flood forecasting. Therefore, using both hydrological models and radar rainfall forecasts can improve the accuracy of flash flood forecasts. In this study, FFG was applied to simulate some flash flood events in the Taehwa river basin by using of SURR model to consider soil moisture, and applied to the flash flood forecasting using predicted radar rainfall. The hydrometeorological data are gathered from 2011 to 2021. Furthermore, radar rainfall is forecasted up to 6-hours has been used to forecast flash flood during heavy rain in August 2021, Wulsan area. The accuracy of the predicted rainfall is evaluated and the correlation between observed and predicted rainfall is analyzed for quantitative evaluation. The results show that with a short lead time (1-3hr) the result of forecast flash flood events was very close to collected information, but with a larger lead time big difference was observed. The results obtained from this study are expected to use for set up the emergency planning to prevent the damage of flash flood.

• Water for future
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• v.29 no.6
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• pp.237-247
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• 1996

In this study two rainfall-runoff models, the NWS-PC model and the Storage Function Model (SFM), were compared to see their applicability in the flood forecasting at the river system. The SFM has been adopted in the flood-forecasting and warning system for the major rivers in Korea since 1974, and the NWS-PC model, a physically based model, has been developed to simulate soil moisture changing as well as the surface and subsurface flow at the watershed and in the river streams. Case studies were carried out using flood event data observed at the Mihochun watershed in Geum-river basin during 1985 to 1995. Simulated results from both models were compared with the observed data with respect to the RMS errors and relative errors for peak flow discharges and total runoff volumes to show the advantages and disadvantages of both models and to suggest the way to improve their performances.

• Journal of Korea Water Resources Association
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• v.31 no.3
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• pp.235-242
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• 1998

The objective of this study is to develope a predictive model for flood forecasting in the tidal reaches of the Nakdong river and to analyze the tidal effects of major flood forecasting station of the Nakdong river by using the hydraulic flood routing. In the calibration process the optimum roughness coefficients as functions of channel reach and discharge were determined and the calibration results suggest that the unsteady hydraulic flood routing model simulated with the optimum roughness coefficients showed close agreement between the calculated and observed stage.

• 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.

• 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.

• Journal of Korea Water Resources Association
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• v.52 no.2
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• pp.107-113
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• 2019

The flood forecasting model currently used in Korea calculates the runoff of basin using the lumped rainfall-runoff model and estimates the river level using the river and reservoir routing models. The lumped model assumes homogeneous drainage zones in the basin. Therefore, it can not consider various spatial characteristics in the basin. In addition, the rainfall data used in lumped model also has the same limitation because of using the point scale rainfall data. To overcome the limitations as mentioned above, many researchers have studied to apply the distributed rainfall-runoff model to flood forecasting system. In this study, to apply the Grid-based Rainfall-Runoff Model (GRM) to the Korean flood forecasting system, the optimal resolution is determined by analyzing the difference of the results of the runoff according to the various resolutions. If the grid size is to small, the computation time becomes excessive and it is not suitable for applying to the flood forecasting model. Even if the grid size is too large, it does not fit the purpose of analyzing the spatial distribution by applying the distributed model. As a result of this study, the optimal resolution which satisfies the accuracy of the bsin runoff prediction and the calculation speed suitable for the flood forecasting was proposed. The accuracy of the runoff prediction was analyzed by comparing the Nash-Sutcliffe model efficiency coefficient (NSE). The optimal resolution estimated from this study will be used as basic data for applying the distributed rainfall-runoff model to the flood forecasting system.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.722-725
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• 2007

Geum River Estuary Barrage is very important for the irrigation, municipal and industrial uses in the cities of Gunsan, Iksan and Jeonju. The Geum River Control Office has a flood forecasting system; however, the current system does not consider the backwater effects. As a result, it is very difficult to give correct flood information, and it is difficult to accurately assess the water resource supply and saltwater invasion into freshwater, as frequently occurs due to over-discharge during floods. In this study, we investigate the flood forecasting system for the Geum River reach influenced by the estuary barrage. The current system cannot consider the backwater effect because the estuary barrage blocks the end of the river. We calculated the discharge from the tide lock and evaluated the inside water level of the estuary barrage during floods. The results show that the calculation agrees well with the observed data at the river stage stations in the Geum River. The results also show that this program is a reasonable substitute for the current system.