• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.437-442
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• 2005

The forecasting of flood runoff in the river is essential for flood control. The purpose of this study is to test a development of system for flood runoff forecasting using neural network model. For the flood events the tested rainfall and runoff data were the input to the input layer and the flood runoff data were used in the output layer To choose the forecasting model which would make up of runoff forecasting system properly, real-time runoff in the river when flood periods were forecasted by using the neural network model and the state-space model. A comparison of the results obtained by the two forecasting models indicated the superiority and reliability of the neural network model over the state-space model. The neural network model was modified to work in the Web and developed to be the basic model of the forecasting system for the flood runoff.

• Journal of Industrial Technology
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• v.3
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• pp.95-101
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• 1983

This study aims at the determination of the coefficienties of runoff and infiltration affecting runoff. The rating curve is more available than the peak flood runoff to determine flood control plan of flood control reservoir and the volume of hydroelectric power plant, or to make multipurpose dam. In hydrologic analysis and design, it is necessary to develop relations between precipitation and runoff, possible using some of the factors affecting runoff as parameters. In order to calculate the runoff discharge, the runoff process constituting elements are divided to the surface runoff, the subsurface runoff and the groundwater runoff. By comparing the computed hydrograph with the measured hydrograph, determinned the watershed TANK Model constant Varying the tank model constant for approximating the computed hydrograph to the measured hydrograph.

• Journal of Korean Society on Water Environment
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• v.29 no.1
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• pp.45-54
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• 2013

This study analyzes the reduction effects of runoff and flood damage through different arrangements of stormwater storage facilities. Three scenarios based on the spatial allocation of storage capacity are used: concentrated, decentralized and combinative. The characteristics of runoff and flood damage by scenario are compared. The XP-SWMM model is used for runoff simulation by the probable rainfall of return period. The result shows that the concentrated arrangement of storage facilities is most effective to reduce the amount of peak flow and to delay the time of peak flow. Yet, while the concentrated arrangement is most effective to reduce the inundation damage, it is not effective to reduce runoff volume. The decentralized arrangement is most effective to reduce runoff volume. The combinative arrangement is effective not only the runoff reduction but also the reduction of flood damage. The result indicates that the flood mitigation strategies against heavy rainfall need to consider decentralized on-site arrangement for the reduction of runoff volume along with concentrated off-site arrangement of storage facilities.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.23-31
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• 2007

The objective of the study is to prepare input data for FIA (Flood Inundation Analysis) & FDA (Flood Damage Assessment) through rainfall-runoff simulation by HEC-HMS model. For HwaOng watershed (235.6 $km^{2}$), HEC-HMS was calibrated using 6 storm events. Geospatial data processors, HEC-GeoHMS is used for HEC-HMS basin input data. The parameters of rainfall loss rate and unit hydrograph are optimized from the observed data. HEC-HMS was applied to simulate rainfall-runoff relation to frequency storm at the HwaOng watershed. The results will be used for mitigating and predicting the flood damage after river routing and inundation propagation analysis through various flood scenarios.

• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.771-780
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• 2004

The purpose of this study is to test a development of system for flood runoff forecasting using neural network model. As the forecasting models for flood runoff the neural network model was tested with the observed flood data at Gongju and Buyeo stations. The neural network model consists of input layer, hidden layer, and output layer. For the flood events tested rainfall and runoff data were the input to the input layer and the flood runoff data were used in the output layer. To make a choice the forecasting model which would make up of runoff forecasting system properly, real-time runoff of river when flood periods were forecasted by using neural network model and state-space model. A comparison of the results obtained by the two forecasting models indicated the superiority and reliability of the neural network model over the state-space model. The neural network model was modified to work in the Web and developed to be the basic model of the forecasting system for the flood runoff. The neural network model developed to be used in the Web was loaded into the server and was applied to the main stream of Geum river. For the main stage gauging stations mentioned above the applicability of the selected forecasting model, the Neural Network Model, was verified in the Web.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.5
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• pp.107-113
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• 2009

The purpose of this study is to estimate the design flood runoff for ungaged forest watershed to reduce the flood damage in national park. Daewonsa watershed in Jirisan National Park was selected as study watershed, of which characteristic factors were obtained from GIS data. Flood runoff was simulated using SCS unit hydrograph module in HEC-HMS model. SCS Curve Number (CN) was calculated from forest type area weighted average method. Huff's time distribution of second-quartile storm of the Sancheong weather station, which is nearest from study watershed, was used for design flood runoff estimation. Critical storm duration for the study watershed was 3 hrs. Based on the critical duration, the peak runoff for each sub-watershed were simulated. It is recommended to monitor the long-term flow data for major stream stations in National Park for a better reliable peak runoff simulation results.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.605-617
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• 2008

This study developed a flood index which evaluates runoff characteristics. Runoff characteristics expressed in a hydrograph were reflected in the flood index in the form of characteristic factors such as a rising curve gradient, a peak discharge, a flood response time, and a flood discharge volume prior to peak. This study applied the standardization method to estimate the relative severity of the characteristic factors by transforming the distribution of characteristic factors into the standard normal distribution. The flood index developed in this study is a comprehensive flood index (CFI) which makes up for the weak points of a flash flood index (FFI) in determining relative severities. The CFI was applied to Han River basin and Selma River basin, and was compared with the FFI based on the correlation analysis and the regression analysis. The CFI could comprehensively evaluate flood runoff characteristics because the CFI is not dominated by a specific characteristic factor, and the CFI could explain more efficiently the relationship between rainfall and runoff than the FFI.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.34-40
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• 1998

The existing flood runoff models, Complex Hydrograph and HEC-1, have some problems which do not properly represent runoff characteristics on the Korean paddy basin and their basin slopes. In this study, FAS(Flood Analysis System) was developed in order to supplement those problems, which was built calibrating runoff curve number for paddy basin and applying basin slopes to classify 5 levels. And also the FAS can synthesize the flood hydrographs of subbasin and analyze flood routing along a stream. To verify the applicability of the FAS, the computed flood hydrographs were compared with the observed hydrographs from the four watersheds. In the small basin smaller than 10$\textrm{km}^2$, the results of the FAS did not completely agree with the observed ones due to concentration time delay of paddy storage effect while in the medium and large size basin showed good agreements between the observed and computed ones. Therefore, it was concluded that the FAS could be applied for the flood analysis of Korean watershed which was characterized by paddy storage effect.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.235-235
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• 2015

This study investigates the impact of event characteristics on runoff dynamics during extreme flood events observed in a $8.5km^2$ experimental watershed located in South Korea. The 37 most extreme flood events with event rainfall in excess of 50 mm were analysed using an event-based rainfall-runoff model; the Revitalised Flood Hydrograph (ReFH) routinely used for design flood estimation in the United Kingdom. The ReFH model was fitted to each event in turn, and links were investigated between each of the two model parameters controlling runoff production and response time, respectively, and event characteristics such as rainfall depth, duration, intensity and also antecedent soil moisture. The results show that the structure of the ReFH model can effectively accommodate any nonlinearity in runoff production, but that the linear unit hydrograph fails to adequately represent a reduction in watershed response time observed for the more extreme events. By linking the unit hydrograph shape directly to rainfall depth, the consequence of the observed nonlinearity in response time is to increase design peak flow by between 50% for a 10 year return period, and up to 80% when considering the probable maximum flood (PMF).

• Journal of Wetlands Research
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• v.12 no.3
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• pp.155-163
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• 2010

The flash flood is characterized as flood leading to damage by heavy rainfall occurred in steep slope and impervious area with short duration. Flash flood occurs when rainfall exceeds Flash Flood Guidance(FFG). So, the accurate estimation of FFG will be helpful in flash flood forecasting and warning system. Say, if we can reduce the uncertainty of rainfall-runoff relationship, FFG can be estimated more accurately. However, since the rainfall-runoff models have their own parameter characteristics, the uncertainty of FFG will depend upon the selection of rainfall-runoff model. This study used four rainfall-runoff models of HEC-HMS model, Storage Function model, SSARR model and TANK model for the estimation of models' uncertainties by using Monte Carlo simulation. Then, we derived the confidence limits of rainfall-runoff relationship by four models on 95%-confidence level.