• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.54-66
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• 2002

A grid-based hydrological model, CELTHYM, capable of estimating base flow and surface runoff using only readily available data, was used to assess hydrologic impacts caused by land use change on Little Eagle Creek (LEC) in Central Indiana. Using time periods when land use data are available, the model was calibrated with two years of observed stream flow data, 1983-1984, and verified by comparison of model predictions with observed stream flow data for 1972-1974 and 1990-1992. Stream flow data were separated into direct runoff and base flow using HYSEP (USGS) to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from simulation results, and the change in these ratios with land use change, shows that the ratio of direct runoff increases proportionally with increasing urban area. The ratio of direct runoff also varies with annual rainfall, with dry year ratios larger than those for wet years shows that urbanization might be more harmful during dry years than abundant rainfall years in terms of water yield and water quality management.

• Journal of Korean Society of Forest Science
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• v.87 no.1
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• pp.11-19
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• 1998

The purpose of this study was to develop the Rainfall-Runoff Model for a long and short term runoff analysis in small forested mountain watersheds. This model was derived from tank model. This model is composed of four tank. Tank I, Tank II, TankIII, and TankIV represent interception loss in forest canopy, direct runoff, base flow, and surface flow component, respectively. This model was tested with two experimental watersheds, located in southern part of Korea. As the result, this model had potentials for simulating and analyzing the long and short term runoff in small forested watersheds.

• Journal of Environmental Science International
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• v.15 no.2
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• pp.141-155
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• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• Water for future
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• v.29 no.6
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• pp.131-139
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• 1996

The main goal of this study is a rainfall-runoff analysis using atopographically-based distributed model. It consists of two parts: one is a direct runoff submodel and the other is a baseflow submodel. The direct runoff submodel is a distributed model which routed through the drainage networks with a kinematic wave model. The baseflow submodel is considered as a lumped system. This model makes it possible to take the effect of areal and temporal distribution of storm into accout.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2215-2219
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• 2009

For model calibration in rainfall-runoff modeling, streamflow data at a specific outlet is obviously required but is not sufficient to identify parameters of a model since numerous parameter combinations can result in very similar model performance measures (i.e. objective functions) and indistinguishable simulated hydrographs. This phenomenon has been called 'equifinality' due to inherent parameter uncertainty involved in rainfall-runoff modeling. This study aims to investigate catchment responses in time and space to various uncertain parameter sets in distributed rainfall-runoff modeling. Seven plausible (or behavioral) parameter sets, which guarantee identically-good model performances, were sampled using deterministic and stochastic optimization methods entitled SCE and SCEM, respectively. Then, we applied them to a computational tracer method linked with a distributed rainfall-runoff model in order to trace and visualize potential origins of streamflow at a catchment outlet. The results showed that all hydrograph simulations based on the plausible parameter sets were performed equally well while internal catchment responses to them showed totally different aspects; different parameter values led to different distributions with respect to the streamflow origins in space and time despite identical simulated hydrographs. Additional information provided by the computational tracer method may be utilized as a complementary constraint for filtering out non-physical parameter set(s) (or reducing parameter uncertainty) in distributed rainfall-runoff modeling.

• 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 The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.9-19
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• 2016

The objective of this study was to evaluate the applicability of SWAT (Soil and Water Assessment Tool) model for runoff estimation in the Nam river dam watershed. Input data for the SWAT model were established using spatial data (land use, soil, digital elevation map) and weather data. The SWAT model was calibrated and validated using observed runoff data from 2003 to 2014 for three stations (Sancheong, Shinan, Changchon) within the study watershed. The $R^2$ (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. Parameters for runoff calibration were selected based on user's manual and references and trial and error method was applied for parameter calibration. Calibration results showed that annual mean runoff were within ${\pm}5%$ error compared to observed. $R^2$ were ranged 0.64 ~ 0.75, RMSE were 2.51 ~ 4.97 mm/day, NSE were 0.48 ~ 0.65, and RMAE were 0.34 ~ 0.63 mm/day for daily runoff, respectively. The runoff comparison for three stations showed that annual runoff was higher in Changchon especially summer and winter seasons. The flow exceedance graph showed that Sancheong and Shinan stations were similar while Changchon was higher in entire fraction.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.907-916
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• 2005

For an urban watershed modeling, the ILLVDAS and SWMM model were the popular rainfall-runoff models using in Korea. However, combined sewerage systems in urban area produce some problems when a flood event happens because of the surcharged precipitation amounts which drain to streams directly. Also, rack of pipe line data and difficulties of modeling yield inappropriate modeling results in urban runoff analysis. In addition, rainfall-runoff models in an urban which using channel routing could be inaccurate and complicated processes. In this paper, the MIKE SWMM model has been applied for a stable urban area runoff analysis. Watershed and pipe line data were established by using past inundated records, DEM data and numerical pipe line data. For a runoff modeling, the Runoff block was adapted to a basin and the Extran block using dynamic equation was applied for sewerage system. After a comparisons against existing models yield that the MIKE SWMM model produce reliable and consistence results without distorting parameter of the model.

• Journal of Environmental Impact Assessment
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• v.3 no.2
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• pp.47-56
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• 1994

AGNPS model is an event-based model to analyze nonpoint-source and to examine potential water quality problems from agricultural watershed. This model uses a square grid-cell system to represent the spatial variability of watershed conditions, and simulates runoff, sediment, and nutrient transport for each cell. AGNPS model was applied on Yeonwha watershed, and the test results were compared with the measured data for runoff volume, peak runoff rate, suspended solids, and phosphorus concentration. The watershed of 278.8 ha was divided into 278 cells, each of which was 1 ha in size. The coefficients of determination for runoff volume and peak flow were (0.893 and 0.801 respectively from regression of the estimated values on the measured values. The concentration of suspendid solid was increased but decreased that of phosphate with runoff volume.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.419-422
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• 2003

The Sumjin Reservoir watershed was simulated by the SSARR model. In order to calibrate the parameters of SSARR model, watershed was divided into three sub-basins with the basin characteristics and the observed runoff datum at estuary of dam were used. As the Results of study, there was not much of difference between the observed runoff and the simulated runoff.