• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.701-709
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• 2000

Integrated storage function model (ISFM) is applied to some rainfall-runoff events of the selected basins in Korea to show validity of the proposed model. Comparing the numerical results of the model with the field measurements, the simulated hydrographs and peak flood discharges for the most part showed good agreements, except the occurrence time of the peak discharges which showed a bit discrepancy, and they showed it was very hard to have a sufficient lead-time to forecast the flood when the upstream inflow of the channel reach was more dominant than the inflow from the residual watershed of the channel.hannel.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.147-147
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• 2022

In January 2021 heavy flood affected South Kalimantan with causing many casualties. The heavy rainfall is predicted to be generated due to the ENSO (El Nino-Southern Oscillation). The weak La-Nina mode appeared to generate more convective cloud above the warmed ocean and result in extreme rainfall with high anomaly compared to past historical rainfall event. Subsequently, the antecedent soil moisture distribution showed to have an important role in generating the flood response. Saturated flow and infiltration excess mainly contributed to the runoff generation due to the high moisture capacity. The hydro-meteorological processes in this event were deeply analyzed using the coupled atmospheric model of Weather Research and Forecasting (WRF) and the hydrological model extension (WRF-Hydro). The sensitivity analysis of the flood response to the SST anomaly and the soil moisture capacity also compared. Result showed that although SST and soil moisture are the main contributors, soil moisture have more significant contribution to the runoff generation despite of anomaly rainfall occurred. Model performance was validated using the Global Precipitation Measurement (GPM) and Soil Moisture Operational Products System (SMOPS) and performed reasonably well. The model was able to capture the hydro-meteorological process of atmosphere and hydrological feedbacks in the extreme weather event.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.280.2-286
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• 1998

Flood is the main natural disaster mostly in the world. It is a care problem to prevent flood disaster generally. The frequency of flood disaster is high and the distributing field is wide, the 50 percent population and 70 percent properties distribute at the threaten field of flood disaster in China. Flood disaster has caused a huge amount of economical losses and these losses have an increasing trend. Along with the development of reducing natural disaster action, it has become one of the most attentive problems for monitoring flood, preventing flood and forecasting flood efficiently. Remote sensing has the characteristics of large spatial observing areas, wide spectrum ranges, and imaging far away from the targets, imaging capabilities all weather. Spatial remote sensing information, which records the full, processes of the disaster's occurrence and development in real-time. It is a scientific basis for management, planning and decision-making. Through systemic analyzing the RS monitoring theory, based on compounding RS information, the technology and method of monitoring flood disaster are studied.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.221-231
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• 2010

A regression water level forecasting model using data from stage and rainfall monitoring stations is developed to solve the difficulties which real-time forecasting models could not get the reliabilities by assuming future rainfall duration and intensity. The model could forecast future water levels of maximum 2 hours after using data from monitoring stations in Daejeon area. It shows stable forecasts by its maximum standard deviation is 5 cm, average standard deviations are 1~4 cm and most of coefficients of determination are larger than 0.95. It shows also more researches about the stationary of watershed which assumed in this regression method are necessary.

• Journal of Korea Water Resources Association
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• v.48 no.5
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• pp.409-423
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• 2015

In this study the very short-term rainfall forecasting and storm water forecasting using the weather radar data were implemented in an urban stream basin. As forecasting time increasing, the very short-term rainfall forecasting results show that the correlation coefficient was decreased and the root mean square error was increased and then the forecasting model accuracy was decreased. However, as a result of the correlation coefficient up to 60-minute forecasting time is maintained 0.5 or higher was obtained. As a result of storm water forecasting in an urban area, the reduction in peak flow and outflow volume with increasing forecasting time occurs, the peak time was analyzed that relatively matched. In the application of storm water forecasting by radar rainfall forecast, the errors has occurred that we determined some of the external factors. In the future, we believed to be necessary to perform that the continuous algorithm improvement such as simulation of rapid generation and disappearance phenomenon by precipitation echo, the improvement of extreme rainfall forecasting in urban areas, and the rainfall-runoff model parameter optimizations. The results of this study, not only urban stream basin, but also we obtained the observed data, and expand the real-time flood alarm system over the ungaged basins. In addition, it is possible to take advantage of development of as multi-sensor based very short-term rainfall forecasting technology.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.331-340
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• 2000

This study aims to develop a methodology of real time forecasting of mundation risk based on DAMBRK model and Kalman filter. The model is based on implicit, nonlinear finite difference approximatIons of the one-dimensional dynamic wave equations. The stochastic estimator uses on extended Kalman filter to provide optimal updating estimates. These are accomplished by combining the predictions of the determurustic model with real time observauons modified by the Kalman filter gain ractor. Inundation risks are also estimated by applying Monte Carlo simulation to consider the variability in cross section geometry and Manning's roughness coefficient. The model calibrated by applying to the floods ot South Han River on September, 1990 and August, 1995. The Kalman tilter model indicates that significant improvement compared to deteriministic analysis in flood routing predictions in the river. Overtopping risk of levee is also presented by comparing levee height with simulated flood level. level.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.746-750
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• 2007

금강홍수통제소는 금강 유역의 홍수피해 경감을 목적으로 1990년 출범하였으며, 개소된 이래로 현재까지 홍수예보 및 수문 관측 업무를 수행하여 왔다. 금강홍수예보시스템의 유출모형은 이미 구축되어 있던 홍수예보 시스템과 마찬가지로 저류함수법과 단위도법에 의한 홍수 유출 모형을 근간으로 구성되어 있다. 최근 증설된 수문관측소를 반영하여 소유역을 재분할하고, 변화된 유역환경을 반영하여 저류함수모형에 대한 상수를 개선하고자 하였다. 소유역 및 하도분할과 티센계수 산정 등을 통해 저류함수법을 이용하기 위한 저류상수를 산정하기 위해 기존의 일반 종이지도로 제작된 지형도(1:50,000), 녹지자연도, 개략토양도 등을 이용하는 대신 수치지도를 이용하여 저류상수를 산정하였다. 새롭게 산정된 유역특성변수를 이용하여 유역의 저류상수를 산정하고 강우에 의한 유출량을 결정하였다. 변화된 유역 조건을 가지고 금강 유역의 전체 유역 및 하도유출계산을 수행한 후, 측정 결과가 있는 지점의 수문곡선과 비교하여 모형상수가 적절히 산정되었는지 검토하고, 개선된 모형상수를 제시하였다.

• Journal of Wetlands Research
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• v.11 no.2
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• pp.107-121
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• 2009

Many rainfall-runoff models have been used for the flood forecasting. However, the determination of rainfall-runoff model parameters is very difficult. In this study, we investigated the efficiency of flood forecasting models by studying the optimization techniques for parameter calibration of SFM, Tank, and SSARR models. We analyzed the correlations between parameters in optimization techniques, then classified the parameters into parameter groups. For this we applied the sequential calibration method through the sensitivity analysis. As the results of the analysis, the parameter groups clibration method showed better result for peak flow and clibtation time.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.207-221
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• 2014

Recently, due to global warming, climate change has affected short time concentrated local rain and unexpected heavy rain which is increasingly causing life and property damage. Therefore, this paper studies the characteristic of localized heavy rain and flash flood in Nakdong basin study area by applying Data Mining method to predict flood and constructing water level predicting model. For the verification neural network from Data Mining method and hydraulic flood routing was used for flood from July 1989 to September 1999 in Nakdong point and Iseon point was used to compare flood level change between observed water level and SAM (Slope Area Method). In this research, the study area was divided into three cases in which each point's flood discharge, water level was considered to construct the model for hydraulic flood routing and neural network based on artificial intelligence which can be made from simple input data used for comparison analysis and comparison evaluation according to actual water level and from the model.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.929-941
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• 2008

The objectives of this study are to propose a system for combined use of a hydrologic and a hydraulic model for urban flood forecast model and to evaluate the system on the $300km^2$ Jungrang urban watershed area, which is relatively large area as an urban watershed and consequently composed of very complex drainage pipes and streams with different land uses. In this study, SWMM for hydrologic model and HEC-RAS for hydraulic model are used and the study area is divided into 25 subbasins. The SWMM model is used for sewer drainage analysis within each subbasin, while HEC-RAS for unstready flow analysis in the channel streams. Also, this study develops a GUI system composed of mean areal precipitation input component, hydrologic runoff analysis component, stream channel routing component, and graphical representation of model output. The proposed system was calibrated for the model parameters and verified for the model applicability by using the observation data. The correlation coefficients between simulated and observed flows at the 2 important locations were ranged on 0.83-0.98, while the coefficients of model efficiency on 0.60-0.92 for the verification periods. This study also provided the possibilities of manhole overflows and channel bank inundation through the calculated water profile of longitudinal and channel sections, respectively. It can be concluded that the proposed system can be used as a surface runoff and channel routing models for urban flood forecast over the large watershed area.