• Journal of Korean Society on Water Environment
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• v.22 no.6
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• pp.977-981
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• 2006

In order to improve water quality in drinking water sources, Ministry of Environment (MOE) was implemented total water pollution load management (TWPLM) in all the major river basins. From the experience of the application of TWPLM, we could find some problems relating the target watershed, standard operating procedure (SOP) of establishment and implementation plan, water quality and flow rate, design flow, water quality model, margin of safety (MOS), and estimation of wasteload were found. The authors were reviewed ongoing TWPLM and presented the improvement schemes for a successful TWPLM. For the application of these suggestions, further detailed studies should be done to implement TWPLM in the future.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.3
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• pp.162-171
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• 2014

In this study, the uncertainty analysis of present land pollutant load estimation with simplified land category in TMDLs was performed and the enhanced method for land pollutant load estimation with level II land cover consisting of 23 categories was suggested, which was verified by L-THIA model. For land TP load estimation in Jinwi stream basin, the result of comparison between existing method with simplified land category (Scenario 1) and enhanced method with level II land cover (Scenario 2) showed high uncertainty in existing method. TP loads estimated by Scenario 2 for land covers included in the site land category were in the range of 3.45 to 56.69 kg/day, in which TP loads differed by sixteen times as much among them. For application of scenario 2 to TMDLs, Land TP loads were estimated by matching level II land cover to 28 land categories in serial cadastral map (Scenario 3). In order to verify accuracy of TP load estimation by scenario 3, the simulation result of L-THIA was compared with that and the difference between the two was as little as 10%. The result of this study is expected to be used as primary data for accurate estimation of land pollutant load in TMDLs.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.728-737
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• 2005

Water quality of the Hwanggujicheon is poor because of the rapid housing and development in the large area of the basin. Establishment of water quality management strategy, based on the pollution sources survey and pollutant loads estimation, has to be established for the preservation of the stream water quality of the region. In this study, waste load allocation model to achieve the water quality goal of the stream and the optimization of pollutant load reduction, was developed. Nonpoint pollutant loads calculated by runoff model in the previous study are utilized for pollutant loads estimation of the drainage areas in this study. From the application result of the allocation model, water quality goals of the Hwanggujicheon that can be achieved as a matter of fact are BOD 8 mg/L. To achieve these goals, 23% of effluent BOD loads have to be reduced in the basin.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.907-915
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• 2010

Agriculture nonpoint pollution source is a significant contributor to water quality degradation. To establish effective water quality control policy, environpolitics establishment person must be able to estimate nonpoint source loads to lakes and streams. To meet this need for orchard area, we investigated a real rainfall runoff phenomena about it. We developed nonpoint source runoff estimation models for vineyard area that has lots of fertilizer, compost specially between agricultural areas. Data used in nonpoint source estimation model gained from real measuring runoff loads and it surveyed for two years(2008-2009 year) about vineyard. Nonpoint source runoff loads estimation models were composed of using independent variables(rainfall, storm duration time(SDT), antecedent dry weather period(ADWP), total runoff depth(TRD), average storm intensity(ASI), average runoff intensity(ARI)). Rainfall, total runoff depth and average runoff intensity among six independent variables were specially high related to nonpoint source runoff loads such as BOD, COD, TN, TP, TOC and SS. The best regression model to predict nonpoint source runoff load was Model 6 and regression factor of all water quality items except for was $R^2=0.85$.

• Journal of Korean Society on Water Environment
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• v.38 no.6
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• pp.306-315
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• 2022

In this study, long-term measurement data were applied to the LOADEST model and used as an analysis tool to identify and interpret trends in pollution load. The LOADEST model is a regression equation-based pollution load estimation program developed by the United States Geological Survey (USGS) to estimate the change in the pollution load of rivers according to flow rate and time and provides 11 regression equations for pollution load evaluation. As a result of simulating the Gwangjuchen2, Pungyeongjeongchen, and Pyeongdongchen in the Yeongbon B unit basin in the middle and upper reaches of the Yeongsan River with the LOADEST model using water quality and flow measurement data, lower values were observed for the Gwangjuchen2 and Pyeongdongchen, whereas the Pungyeongjeongchen had higher values. This was judged to be due to the characteristics of the LOADEST model related to data continuity. According to the parameters estimated by the LOADEST model, pollutant trends were affected by increases in the flow. In addition, variability increased with time, and BOD and T-P were affected by the season. Thus, the LOADEST model can contribute to water quality management as an analytical tool for long-term data monitoring.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.4
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• pp.19-26
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• 2010

To provide the basic information for the water quality management of the Sumjin River Basin, delivery ratios for flow duration were studied. Using the day-interval data set of discharge and water quality observed from the Chooryeong-cheon watershed, the flow-duration and discharge-load relation curves for the watershed were established, then the load-duration curve was constructed. Delivery ratios for flow duration were also developed. Delivery ratios showed wide variation according to flow conditions. In general, delivery ratio of high flow condition showed higher value reflecting nonpoint source pollution contribution from the forest dominating watershed. To resolve this problem, a regression model explaining the relation between flow rate and delivery ratio was suggested. The delivery ratios for different flow regime could be used for pollutant load estimation and TMDL (Total maximum daily load) development.

• Journal of Environmental Science International
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• v.15 no.10
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• pp.951-960
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• 2006

The eco-hydrodynamic model was used to estimate the environmental capacity in Gamak Bay. It is composed of the three-dimensional hydrodynamic model for the simulation of water flow and ecosystem model for the simulation of phytoplankton. As the results of three-dimensional hydrodynamic simulation, the computed tidal currents are toward the inner part of bay through Yeosu Harbor and the southern mouth of the bay during the flood tide, and being in the opposite direction during the ebb tide. The computed residual currents were dominated southward flow at Yeosu Harbor and sea flow at mouth of bay, The comparison between the simulated and observed tidal ellipses at three station showed fairly good agreement. The distributions of COD in the Gamak bay were simulated and reproduced by an ecosystem model. The simulated results of COD were fairly good coincided with the observed values within relative error of 1.93%, correlation coefficient(r) of 0.88. In order to estimate the environmental capacity in Gamak bay, the simulations were performed by controlling quantitatively the pollution loads with an ecosystem model. In case the pollution loads including streams become 10 times as high as the present loads, the results showed the concentration of COD to be $1.33{\sim}4.74mg/{\ell}(mean\;2.28mg/{\ell})$, which is the third class criterion of Korean standards for marine water quality In case the pollution loads including streams become 30 times as high as the present loads, the results showed the concentration of COD to be $1.38{\sim}7.87mg/{\ell}(mean\;2.97mg/{\ell})$, which is the third class criterion of Korean standards for marine water quality. In case the pollution loads including streams become 50 times as high as the present loads, the results showed the concentration of COD to be $1.44{\sim}9.80mg/{\ell}(mean\;3.56mg/{\ell})$, which is the third class criterion of Korean standards for marine water quality.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.12
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• pp.1265-1273
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• 2006

The environmental capacity and watershed pollution load reduction of Yongdam reservoir were estimated by the simulation of water quality variation process with the target water quality establishment, pollution load estimation and flow analysis. The potable raw water $I{\sim}II$, COD $1.0{\sim}3.0$ mg/L and TP $0.01{\sim}0.03$ mg/L were selected as the target water quality Yongdam reservoir water quality model was constructed with WASP5 contained 42 segments and the correlation of calibrated results were BOD 0.73, $PO_4-P$ 0.98. The environmental capacity for target quality COD 2.0 mg/L and TP 0.02 mg/L were BOD $131,880{\sim}4,694$ kg/d, TP $7,855 {\sim}167$ kg/d which were less than exists, and the related reduction ratios were BOD $51{\sim}62%$, TP $47{\sim}67%$ which were middle amount in exists. The load reduction ratios to meet the potable raw water $I{\sim}II$ were BOD $72{\sim}16%$, TP $78{\sim}36%$ in existing conditions and BOD $81{\sim}44%$, TP $84{\sim}52%$ in new conditions. BOD was the least one and TP was the second least in 4 results. The effects of the load reduction assignment to subbasin were dominant in TP but little in COD.

• Journal of Korean Society of Rural Planning
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• v.7 no.1 s.13
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• pp.27-36
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• 2001

Estimation of current and future loading from watershed is necessary for the sound management of water quality of an estuary lake. Pollution sources of point and non-point source pollution were surveyed and Identified for the Koheung watershed. Unit factor method was used to estimate potential pollutant load from the watershed of current conditions. Flow rate and water qualify of base flow and storm-runoff were monitored in the main streams of the watershed. Estimation of runoff pollutant loading from the watershed into the lake in current conditions was conducted by GWLF model after calibration using observed data. Prospective pollutant loading from the reclaimed paddy fields under cultivation conditions was estimated using the modified CREAMS model. As a result, changes of pollutant loading into estuary lake according to non-cultivation and cultivation conditions of reclaimed tidal land were estimated.

• Journal of Korean Society on Water Environment
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• v.30 no.4
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• pp.418-428
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• 2014

The purpose of this study is to predict the spatio-temporal changes in land uses and to evaluate land-based pollutant loads in the future under Total Water Pollution Load Management System using CLUE-S model. For these ends, sensitive parameters of conversion elasticities in CLUE-S model were calibrated and these calibrated parameters of conversion elasticities, level II land cover map of year 2009, and 7 driving factors of land use changes were used in predicting future land uses in 2002 with two scenarios(Scenario 1: non area restriction, Scenario 2: area restriction). This projected land use map of 2020 was used to estimate land-based pollutant loads. It was expected that urban areas will increase in 2020 from both scenarios 1 and 2. In Scenario 1, urban areas are expected to increase within greenbelt areas and deforest would be expected. Under Scenario 2, these phenomena were not expected. Also the results of estimation of BOD and TP pollutant loads, the BOD difference between scenarios 1 and 2 was 719 kg/day in urban areas and TP difference was 17.60 kg/day in urban areas. As shown in this study, it was found that the CLUE-S model can be useful in future pollutant load estimations because of its capability of projecting future land uses considering various socio-economic driving factors and area-restriction factors, compared with conventionally used land use prediction model.