• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.1-9
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• 2008

The impact of snow accumulation and snowmelt in rainfall-runoff modelling was analyzed for the Soyanggang dam basin by comparing the measured and simulated discharges simulated by the NWS-PC model. Sugawara's conceptual model was used to simulate the snow accumulation and snowmelt phenomena and NWS-PC model was employed to simulate rainfall-runoff. Parameters in model calibration were estimated by the Multi-step Automated Calibration Scheme and optimized using SCE-UA algorithm in each step. The results of the model calibration and verification show that the model considering snowmelt process is better than the one without consideration of snowmelt under the performance criteria such as RMSE, PBIAS, NSE, and PME. The measured discharge time series has over 60 days of persistence. Correlograms for each simulation showed that the simulated discharge with snowmelt model reproduce the persistence closely to the measured discharge's while the one without snow accumulation and snowmelt model reproduce only 20 days of persistence. The study result indicates that the inclusion of snow accumulation and snowmelt model is important for the accurate simulation of rainfall-runoff phenomena in the Soyanggang dam basin.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.128-133
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• 2002

• Journal of Korean Society on Water Environment
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• v.22 no.6
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• pp.1088-1093
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• 2006

In this study, the method of annual sediment estimation for reservoir long-term operation is proposed. Long-term daily precipitation and evaporation are predicted by Markov Chain. Using these values, reservoir inflow is simulated by NWS-PC model. Reservoir sediment load is estimated by sediment rating relation curve which is observed. From the simulation results, it was found that each simulated value by Markov Chain and NWS-PC was well compared to the observed ones and also estimated reservoir sediment was appropriate to the compared values using empirical equations. It is thought that the proposed method for estimation of reservoir sediment can be useful used to operate the reservoir.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.383-392
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• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• Proceedings of the Korea Water Resources Association Conference
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• 1998.05a
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• pp.672-677
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• 1998

• Journal of Korea Water Resources Association
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• v.38 no.2
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• pp.97-110
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• 2005

This paper presents a procedure of evaluation of reservoir capacity for additional water storage for dam rehabilitation. One of the techniques on the extension of rainfall has been developed, and the daily stream flows were simulated by the NWS-PC long-term rainfall-runoff model with the input of the extended daily rainfall which was stochastically generated by the nonhomogeneous markov chain model. We peformed a reliability analysis to Guisan dam about the optimal capacity of dam rehabilitation by using performance criteria that Hashimoto et al. (1982) presented. We estimated that the most suitable water level is approximately 155EL.M. suggested that this method can use supplemental methods to estimate optimum dam scale.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.75-82
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• 1997

The stream morphologic characteristics of Wonju stream with small watershed are developed with a regular correlation referred to the Horton-Strahler's lows of stream order. Using Manning's formula and the discharges simulated by NWS-PC rainfallrunoff model that has been applied to the adjacent basin for model calibration and verification, the hydraulic characteristics at Wonju bridge are investigated. The peak discharge and the time to peak of unit hydrograph are analyzed by the calculated geomorphologic parameters. Rather primitive as this study is, these results are provided to be used for geomorphologic instantaneous unit hydropraph of ungaged basins including this study area. Through the reestablishment of rating curve and hydrograph with continuous field observations, the hydrologic and hydraulic characteristics of Wonju stream must be presented.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.723-726
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• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established, uncertainty analysis, therefore, are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an expected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.2 s.40
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• pp.33-42
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• 2007

A physical-based aggregation method was suggested to estimate surface roughness, which adequately represents the spatial heterogeneity of vegetation factors, from land cover property obtained from the remote sensing data. For the sensitivity analysis of surface roughness, the peak flow, peak time, and total volume were simulated by the NWS-PC. Effects of surface roughness estimated by three different integration methods (predominant, arithmetic mean, and aggregation approach) on the conceptual rainfall-runoff model parameters was analyzed. In the preliminary sensitivity test to surface roughness, the peak time had 10% variation and total volume had 2% variation. The peak time increased with surface roughness. A physical-based aggregation method was better than the existing method in the Soyanggang Dam basin for the results of STDEV, RMSE, NSE, and PME, but difference between them were small. The parameters related on the total baseflow were changed significantly with change of the surface roughness.