• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.475-475
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• 2022

The aim of this study is to identify the significant pollutant sources from the tributaries that are affecting the water quality of the study site, the Geum River and provide a solution to enhance the water quality. Multivariate statistical analysis modles such as cluster analysis, Principal component analysis (PCA) and positive matrix factorization (PMF) were applied to identify and prioritize the major pollutant sources of the two major tributaries, Gab-cheon and Miho-cheon, of the Geum River. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant (WWTP), urban, and agricultural pollutions are identified as major pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. On the contrary, PMF identifies three pollutant sources in Gab-cheon, same as PCA result and two pollutant sources in Miho-cheon. Water quality control scenarios are formulated and improvement of water quality in the river locations are simulated and analyzed with the Environmental Fluid Dynamic Code (EFDC) model. Scenario results were evaluated using a water quality index developed by Canadian Council of Ministers of the Environment. PCA and PMF appears to be effective to identify water pollution sources for the Geum river and also its tributaries in detail and thus can be used for the development of water quality improvement alternative of the above water bodies.

• Journal of Environmental Science International
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• v.23 no.1
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• pp.7-23
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• 2014

This study estimates unit for the nonpoint source(NPS), classified according to the existing Level-1(large scale) land cover map, by monitoring the measurement results from each Level-2(medium scale) land cover map, and verifies the applicability by comparison with previously calculated units using the Level-1 land cover map. The NPS pollutant loading for a basin is evaluated by applying the NPS pollutant unit to Dongcheon basin using the Level-2 land cover map. In addition, the BASINS/HSPF(Better Assessment Science Integrating point & Non-point Sources/Hydrological Simulation Program-Fortran) model is used to evaluate the reliability of the NPS pollutant loading computation by comparing the loading during precipitation in the Dongcheon basin. The NPS pollutant unit for the Level-2 land cover map is computed based on precipitation measured by the Sangju observatory in the Nakdong River basin. Finally, the feasibility of the NPS pollutant loading computation using a BASINS/HSPF model is evaluated by comparing and analyzing the NPS pollutant loading when estimated unit using the Level-2 land cover map and simulated using the BASINS/HSPF models.

• Journal of Korean Society on Water Environment
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• v.31 no.1
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• pp.55-66
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• 2015

It has been well known that it is not easy to quantify pollutant loads driven by non-point source pollution due to various factors affecting generation and transport mechanism of it. Especially pollutant loads through baseflow have been investigated by limited number of researchers. Thus in this study, the Web-based WAPLE (WHAT-Pollutant Load Estimation) system was developed and applied at study watersheds to quantify baseflow contribution of pollutant. In YbB watershed, baseflow contribution with WWTP discharge is responsible for 49.5% of total pollutant loads at the watershed. Among these, pollutant loads through baseflow (excluding any WWTP discharge) is responsible for 61.7% of it. In GbA watershed, it was found that 58.4% is contributed by baseflow with WWTP discharge 2.9% and 97.1% is by baseflow. For NbB watershed (without WWTP discharge), 52.3% of pollutant load is transported through baseflow. As shown in this study, it was found that over 50.0% of TN (Total Nitrogen) pollutant loads are contributed by non-direct runoff. Thus pollutant loads contributed by baseflow and WWTP discharge as well as direct runoff contribution should be quantified to develop and implement watershed-specific Best Management Practices during dry period.

• Journal of Environmental Impact Assessment
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• v.12 no.5
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• pp.349-358
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• 2003

Water pollution of Hwanggujicheon stream is severe because urban area of Suwon City is included in the basin. A countermeasure for water quality prevention of the stream is necessary. In this study, nonpoint pollutant load of BOD, SS, TN and TP are estimated using SWMM. The result indicates that BOD, SS, TN and TP loads during 3 months from July to September are 67.0%, 60.8%, 54.7% and 74.5% of the annual total load, respectively. We can see that most of nonpoint pollutant loads are generated in the rainy season. Annual nonpoint pollutant loads of BOD, SS, TN and TP in the Hwanggujicheon stream are 342 ton, 1,500 ton, 480 ton and 12.6 ton, respectively.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.13-17
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• 2019

This study was conducted to analyse the application of pollutant build-up model on various urban landuses and to characterize pollutant build-up on urban areas as a source of stormwater runoff pollution. The monitored data from impervious surfaces in urban areas such as commercial (8 sites), industrial (10 sites), road (8 sites), residential (10 sites), recreational (5 sites) from 2008 to 2016 were used for the analysis of pollutant build-up model. Based on the results, the average runoff coefficients vary from 0.35 to 0.61. In all landuses except recreational landuse, the runoff coefficient is 0.5 or more, which is the highest in the commercial area. Commercial landuse where pollutants occur at the highest EMC in all landuse, and it is considered that NPS management is necessary compared with other landuses. The maximum build-up load for organic matter (BOD) was highest in the commercial area ($4.59g/m^2$), and for particular matter (TSS) in the road area ($5.90g/m^2$) while for nutrient (TN and TP) in the residential area ($0.40g/m^2$, $0.14g/m^2$). The rate constants ranged from 0.1 to 1.3 1/day depending on landuse and pollutant parameters, which means that pollutant accumulation occurs between 1 and 10 days during dry day. It is clear that these build-up curves can generally be classified based on landuse. Antecedent dry day (ADD) is a suitable and reasonable variable for developing pollutant build-up functions. The pollutant build-up curves for different landuse shows that these build-up curves can be generally categorized based on landuse.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.239-248
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• 2000

The aggravating water quality from the expansion of industrialization along with increasing population lead to develop more intensive physical measures to secure better drinking water quality. This study was mainly initiated to establish a water-pollutant buffering zone for the upper stream basin of Paldang--the major source area of drinking water for the metropolitan Seoul and suburban areas with a population more than 13 million. Two different criteria were considered in determining the buffering distance from the edge of the streamflow : 1km-width buffer zone for the special protection area which has been strictly controlled by the conventional laws for the protection of drinking water supply, and 500m-width buffer zone for the rest of the area. To delineate the exact boundaries of the water-pollutant buffering zone, GIS database was created integrating topography, hydrography, cadastral, and other related layers. The newly designated water-pollutant buffering zone would contribute to improve the water quality in a long term along with the conservation of the wet land. More study, however, should be made within the water-pollutant buffering zone such as the detailed survey of the pollutants, vegetation, and ecosystem for more effective management of the buffering zone.

• Journal of environmental and Sanitary engineering
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• v.23 no.3
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• pp.47-57
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• 2008

This study was predicted the diffusion of the conservative contaminant using a two-dimensional hydraulic model. The research area is upper basin of Jakwang river where the possibility where the pollutant of vast quantity will flow is high. Using SMS model, we calculated two-dimensional stream flow. And using this result, predicted the conduct of the conservative contaminant by pollutant transfer diffusion calculation. And also we predicted flow and contaminant diffusion in the near estuary by constructed guide bank. As a result of study, pollutant effect scope of the conservative contaminant was predicted with the fact that will broaden because of interception by guide bank. As discharge was increased from the Jakwang river, The diffusion of the pollutant is accelerated, also the effect scope increases.

• Journal of Urban Science
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• v.10 no.1
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• pp.39-48
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• 2021

In this study, to evaluate the characteristics of the pollution in the major inflow tributaries and major environmental facilities in the watershed of Ara waterway, An inflow flow rate measurement and water quality analysis were conducted during dry and rainy seasons. In addition, the flow rate measurement, water quality analysis, and pollutant load at each monitoring point were compared and evaluated. Influx of BOD5, T-P and T-N into the tributaries of the ARA waterway watershed, excluding the Gulpo river watershed, during dry season were only 0.007%, 0.005% and 0.004% respectively of the incoming loads in the entire ARA waterway basin. In addition, it was confirmed that the discharge pollutant loads during rainfall event was about 440 times more for BOD5, about 545 times on T-P, and about 23 times on T-N in comparison to the pollutant loads during the dry days. When the Gulhyeon rubber dam was deflated, the discharged pollutant load during a rainfall was higher than the estimated load at the G7 monitoring point because the deposited pollutants from the upstream riverbed flowed down. Therefore, during a rainy season, it is necessary to manage the influx of high-load water pollutants from the overflow and deflation of the Gulhyun rubber dam as well as to find a strategy to reduce the pollutant loads in the Gulpo river watershed.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2910-2916
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• 2011

Environmental conservation is becoming the major conversation topic in the 21st century, the era of environment. In the Law for the Preservation of Water Quality, article 53 states "A business unit which is doing business causing pollution caused by non-point pollutant or builds waste water discharge facilities, should report the installation of the non-point pollutant and install the required pollution control facilities". Environmental pollution caused by oil leaks during operation or maintenance has been found in the railway sector. Especially, rolling stock depot is most likely to be affected by environmental pollution. Therefore, in this paper We have investigated non-point pollutant in the rolling stock depot area and have studied adequate disposal method to minimize the effect of the non-point pollutant, hoping to supply the preliminary data for building an environment-friendly rolling stock depot.