• Magazine of the Korean Society of Agricultural Engineers
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• v.28 no.2
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• pp.42-52
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• 1986

This study involves the estimation of optimal ranges of parameters for a linear watershed model. A well-known TANK model was chosen and a linear combination of four tanks assumed. The model was used to simulate daily streamflow for six watersheds of different sizes and by a trial-and-error approach a set of optimal parameters defined. The parameters were related to watershed sizes and land use conditions. Optimal parameters for ungaged conditions were defined from the relationships; daily streamflow simulated and compared to the observed date. The simulated results were in a general agreement with the data.

• Journal of Korean Society on Water Environment
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• v.29 no.1
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• pp.36-44
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• 2013

HSPF model based on BASINS was applied to analyze effects of watershed management measures for water quality conservation in the Hwaseong Reservoir watershed. The model was calibrated against the field measurements of meteorological data, streamflow and water qualities ($BOD_5$, T-N, T-P) at each observatory for 4 years (2007-2010). The water quality characteristics of inflow streams were evaluated. The 4 scenarios for the water quality improvement were applied to inflow streams and critical area from water pollution based on previous researches. The reduction efficiency of point and non-point sources in inflow streams was evaluated with each scenario. The results demonstrate that the expansion of advanced treatment system within wastewater treatment plants (WWTPs) and construction of pond-wetlands would be great effective management measures. In order to satisfactory the target water quality of reservoir, the measures which can control both point source and non-point source pollutants should be implemented in the watershed.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.2
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• pp.61-74
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• 2007

A mathematical modeling program called Hydrological Simulation Program-FORTRAN (HSPF) developed by the United States Environmental Protection Agency (EPA) was applied to Hwaseong watershed. It was run under BASINS (Better Assessment Science for Integrating Point and Nonpoint Sources) program, and the model was validated using monitoring data of $2002{\sim}2005$. The model efficiency of runoff ranged from good to fair in comparison between simulated and observed data, while it was from very good to poor in the water quality parameters. But its reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The nonpoint source (NPS) loading for T-N and T-P during the monsoon rainy season (June to September) was about 80% of total NPS loading, and runoff volume was also in a similar range. However, NPS loading for BOD ($55{\sim}60%$) didn't depend on rainfall because BOD was mostly discharged from point source (more than 70%). And water quality was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. BASINS/HSPF was applied to the Hwaseong watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and nonpoint sources in watershed scale.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.984-993
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• 2009

There have been growing concerns of algal growth at Daecheong reservoir due to eutrophication with excess nutrient inflow. Rainfall-driven runoff and pollutant from watershed are responsible for eutrophication of the Daecheong reservoir. In this study, two subwatersheds of the Daecheong reservoir were selected and water quality characteristics were analyzed. The L-THIA ArcView GIS model was used for evaluation of direct runoff and water quality. The $R^2$ and the EI value for direct runoff were 0.95 and 0.93 at Wol-oe watershed and were 0.81, 0.71 at An-nae watershed, respectively. The $R^2$ for SS, T-P were 0.53, 0.95 at Wol-oe watershed and 0.89, 0.89 at An-nae watershed, respectively. It has been proven that the L-THIA ArcView GIS model could be used for evaluating direct runoff and pollutant load from the watershed with reasonable accuracies.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.1
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• pp.1-11
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• 2010

Generation and transportation of runoff and pollutant loads within watershed generated eutrophication at Daecheong reservoir. To improve water quality at Daecheong reservoir, the best management practices should be developed and applied at upper watersheds for water quality improvement at downstream areas. In this study, two small watersheds of upper Daecheong reservoir were selected. The Long-Term Hydrologic Impact Assessment (L-THIA) model has been widely used for the estimation of the direct runoff worldwide. To apply the L-THIA ArcView GIS model was evaluated for direct runoff and water quality estimation at small watershed. And the Web-based Hydrograph Analysis Tool (WHAT) was used for direct runoff separating from total flow. As a result, the $R^2$ (Coefficient of determination) value and Nash-Sutcliffe coefficient value for direct runoff comparison at An-nae watershed were 0.81 and 0.71, respectively. And the $R^2$ value and Nash-Sutcliffe coefficient value at Wol-oe were 0.95 and 0.93. The $R^2$ value of BOD, TOC, T-N and T-P at An-nae watershed were BOD 0.94, TOC 0.81, T-N 0.94 and T-P 0.89. And the $R^2$ value of BOD, TOC, T-N and T-P at Wol-oe watershed were BOD 0.80, TOC 0.93, T-N 0.86 and T-P 0.65. The result that estimated pollutant loadings using the L-THIA ArcView GIS model reflected well the measured pollutant loadings except for T-P in Wol-oe watershed. With L-THIA ArcView GIS model, the direct runoff and non-point pollutant (NPS) loadings in the watershed could be analyzed through simple input data such as daily rainfall, land uses, and hydrologic soil group.

• Journal of Environmental Science International
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• v.17 no.9
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• pp.1039-1052
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• 2008

The SWAT model developed by the USDA-Agricultural Research service for the prediction of rainfall run-off, sediment, and chemical yields in a basin was applied to Jeju Island watershed to estimate the amount of runoff. The research outcomes revealed that the estimated amount of runoff for the long term on 2 water-sheds showed fairly good performance by the long-term daily runoff simulation. The watershed of Chunmi river located the eastern region in Jeju Island, after calibrations of direct runoff data of 2 surveys, showed the similar values to the existing watershed average runoff rate as 22% of average direct runoff rate for the applied period. The watershed of Oaedo river located the northern region showed $R^2$ of 0.93, RMSE of 14.92 and ME of 0.70 as the result of calibrations by runoff data in the occurrence of 7 rainfalls.

• Spatial Information Research
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• v.10 no.2
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• pp.263-273
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• 2002

This paper presents desirable water environmental management to a closed watershed. In order to obtain spatially distributed environmental information, GIS data have been used. Elevation data are used to extract stream channels automatically and to divide networks of a watershed. A Digital Elevation Model (DEM) has been developed, validated, and adopted to estimate the runoff of total nitrogen pollutant from watershed. This GIS-linked model can be applied effectively to the watersheds with many sub-streams, and for the estimation of pollutant runoff considering land use change.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.10
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• pp.551-557
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• 2015

This study analyzes potentially hazardous sub-watersheds from non-point source pollution areas using an HSPF model. The watershed of the Juam dam reservoir was divided into 29 sub-watersheds, and the flow, BOD, TN and TP concentration for the Juam dam watershed were evaluated from 2009 to 2012 using a watershed model, with a warming period from 2009 to 2010. The results of the watershed model agreed well with the flow and water quality field measurements. The calculated average non-point source loadings were BOD of 8.8 and $9.1kg/day/km^2$ in 2011 and 2012, respectively; TN of 9.7 and $10.1kg/day/km^2$ in 2011 and 2012, respectively; and TP of 0.30 and $0.33kg/day/km^2$ in 2011 and 2012, respectively. The non-point source loading of the Bonghwa stream watershed was calculated, and predominantly assessed upstream of the Boseong river. Additionally, the Miryeok, Jangpyeong, Yuleo, Guam, Seokgyo, Mundeok, Incheon, and Bongnae stream watersheds, with extensive agricultural areas, were assessed to be potentially hazardous areas in terms of non-point source management. In this study, HSPF model was applied in order to aid in the selection of non-point source reduction facilities for the Juam dam watershed, where they were evaluated as to whether they would be applicable for non-point source management.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.63-74
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• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

• Water for future
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• v.17 no.2
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• pp.125-131
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• 1984

watershed Model by mathematical formulation is one of the powerful tool to analyze the hydrologic process in a watershed. The seasonal watershed model is one of the mathematial model from which the monthly streamflow can be simulated and forcasted for given precipitaion data. This model also enables us to compute the monthly runoff at each subbgasin when the basin is subdivided into several small subbasins. The computation of runoff volume makes a Prediction of the areal distirbution of runoff volume for a given precipitation data. Several basins in Han River basin were chosen to simulate the monthly runoff and compute the runoff at each subbasin. A simple logarithmic regression were conducted between runoff ratio and area ratio. The correlation was very high and the equation can be used for prediciting flood volume when flood at downstream gaging station is know.