• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.597-604
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• 2011

This research analyzed the runoff patterns and estimated unit loads of selected pollutatnts using monitored data conducted for three years in a bridge area. Three estimating methods; the arithmetic average method, the regression method and the rainfall class method were used to estimate the unit load. Results of three estimating methods were compared with the unit pollutant loads from landuses in Korea and the unit pollutant loads from urban watersheds in Milwaukee, USA. Unit load using the arithmetic mean method were found to be overestimated. In terms of TSS, unit loads of two estimate were half lower than that of USA. Estimated TN and TP unit loads of three estimate were lower than that of Ministry of Environment in Korea.

• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.175-189
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• 2021

In this study, 48 streams in the Sapgyo Watershed were selected, and the Load Duration Curves (LDC) were drawn up for each stream using water quality and flow monitoring over the last three years (2018-2020), and it was evaluated whether the target water quality was achieved for each flow section. As a result of evaluating whether or not the target water quality exceeded according to the LDC, it was found that 22 rivers exceeded the target water quality. Five rivers exceeded the target water quality due to point pollutant sources, 13 rivers exceeded the target water quality due to non-point pollutant sources, and 4 rivers exceeded the target water quality due to both point and non-point pollutant sources. Among the rivers that exceeded the target water quality due to point pollutant sources, which included domestic sewage of the untreated population, there is a need to reduce the influx of polluted loads by the untreated population. The use of eco-friendly fertilizers is recommended for rivers with a relatively high farmland ratio among rivers exceeding the target water quality due to non-point pollutant sources, and installation of boiling point reduction facilities that can reduce the amount of polluted load introduced during rainfall or manage water shores. In rivers with a large number of livestock breeding heads, the livestock houses located in these rivers need to be preferentially transferred to livestock manure treatment plants. Due to the high ratio of land area because of urbanization, initial rainwater treatment facilities are required to reduce the amount of pollutant load flowing into the river through the impermeable layer during rainfall.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.1-4
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• 2001

The classification performance of Artificial Neural Network (ANN) and RBF-NN was compared for Landsat TM image. The RBF-NN was validated for three unique landuse types (e.g. Mixed landuse area, Cultivated area, Urban area), different input band combinations and classification class. The bootstrap resampling technique was employed to estimate the confidence intervals and distribution for unit load, The pollutant generation was varied significantly according to the classification accuracy and percentile unit load applied. Especially in urban area, where mixed landuse is dominant, the difference of estimated pollutant load is largely varied.

• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.37-43
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• 2014

BACKGROUND: Water quality data are collected less frequently than flow data because of the cost to collect and analyze, while water quality data corresponding to flow data are required to compute pollutant loads or to calibrate other hydrology models. Regression models are applicable to interpolate water quality data corresponding to flow data. METHODS AND RESULTS: A regression model was suggested which is capable to consider flow and time variance, and the regression model coefficients were calibrated using various measured water quality data with genetic-algorithm. Both LOADEST and the regression using genetic-algorithm were evaluated by 19 water quality data sets through calibration and validation. The regression model using genetic-algorithm displayed the similar model behaviors to LOADEST. The load estimates by both LOADEST and the regression model using genetic-algorithm indicated that use of a large proportion of water quality data does not necessarily lead to the load estimates with smaller error to measured load. CONCLUSION: Regression models need to be calibrated and validated before they are used to interpolate pollutant loads, as separating water quality data into two data sets for calibration and validation.

• Journal of Korean Society on Water Environment
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• v.32 no.4
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• pp.375-383
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• 2016

Total Pollution Load Control (TPLC) calculates and manages the allowable pollutant load that is discharged from the watershed, which can meet the water quality target. Delivery Ratio (DR) is generally used for predicting the variation of pollutant mass balance between the pollutants discharged from the watershed and a certain point in the stream, and it is very important for estimation of accurate allowable pollutant load. The concept of DR in TPLC is different from prevalent DR, because DR in TPLC includes both the discharge of pollutants from the watershed and the delivery mechanism. Therefore, DR in TPLC should be estimated by using a proper and unified methodology. The appropriate method and equation for estimation of DR in TPLC was developed through the review of various methodologies, and the applicability of the equation was evaluated in a study area (Geumho A). Determination coefficients (R²) of regression were shown to be relatively high (BOD 0.71~0.87, T-N 0.86~0.90, T-P 0.62~0.69). Applicability of the developed methodology and equations was evaluated as appropriate for TPLC, and it is suggested.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.509-515
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• 2011

For this study the 4 sub-watersheds Okdong A, Hankang B, Jecheon A and Hankang C which are the main streams of the Han River within the mid-level region of Chungju Dam are selected and the analysis of soils has been carried out through the soil basic survey. When it comes to the soil erosion amount the soil nutrient load has been calculated by utilizing the RUSLE erosion equation. In case of the data related to the measurement of water flow and quality the information available from the "Water Information System" one of the websites run by the Ministry of Environment has been used to calculate the water pollution load. The correlation between the soil nutrient load and the water pollutant load has been analyzed through making comparison. According to the results related to the soil nutrient load of each sub-watershed the Hankang C shows the highest values TOC 29,986.92 ton/yr, TN 3,860.33 ton/yr and TP 973.97 ton/yr respectively. Even when it comes to the loads related to water quality the Hankang C shows also comparatively high values TOC 6,625.64 ton/yr, TN 7,335.01 ton/yrand TP 145.49 ton/yr respectively. The soil nutrient loads of the sub-watersheds are shown to increase towards the lower stream meaning the load increases in the order of Hankang CHankang B and Okdong A. When it comes to the water pollutant load the value goes up along down the water system meaning the load gets higher in the order of Hankang C, Hankang B and Okdong A while utilizing the mainstream within the mid-level region of Chungju Dam as the basis. The correlation study showed that the nutrient content of soil is proportional to the pollutant load in water with the strongest positive correlation with TOC.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.533-540
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• 1998

In this study, to propose the methods predicting water qualities in rural areas, the methods which were based on the runoff ratio, the relationships between the pollutant load(L) and the water runoff(Q), and the relationships between the runoff ratio and the water runoff in Bokha stream watersheds were examined. As a result, we had acquired reliable the values of runoff ratio and the reasonable equations between the pollutant load(L) and the water runoff(Q) in Bokha stream watersheds. And it was noticed that the runoff ratio had tendency of varying directly proportional to the water runoff.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.701-707
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• 1999

This study was initiated to collect background pollutant data for rural watersheds. The effluent/run-off polutant load and run-off ratio of the study areas were calculated and the two types of regression equations, L=a$.$Q+b and L=c$.$Qd where L and Q are the pollutant load(L) and discharge (Q), were derived. We acquired that the correlation coeffcients of the two types of regression equations were over than 90% except for BOD . Therefore, L-Q equations would be a measure to predict water quality of rural watersheds.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.3
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• pp.9-14
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• 2009

Flow and pollution load were monitored at 2 combined sewer outlets (C-1 and C-2) of urban watersheds during dry weather from September, 2004 to April, 2006 for 20 months. The objectives were to investigate the diurnal variation of flow and pollutant load and to find the proper sampling time that could measure representative flow and pollutant load. Pollution load closed to the average daily load at C-1 could be measured at 00:00 hour and by the mean of 15:00 and 18:00 hour measures, and 15:00 and 21:00 hour measures, respectively. In addition at C-2, it was 21:00 hour and the mean of 15:00 and 18:00 hour measures. This study concluded that arbitrary sampling of flow and water quality could cause large errors in the estimation of urban pollution load and recommended that urban combined sewers should be monitored when flow and water quality showed daily average and concentration.

• Journal of Korean Society on Water Environment
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• v.28 no.6
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• pp.819-832
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• 2012

HSPF model based on BASINS was applied for the Hwaseong Reservoir watershed (HRW) to evaluate the feasibility of water quality management. The watershed was divided into 45 sub-basins considering various watershed environment. Streamflow was calibrated based on the measured meteorological data, discharge data of treatment plants and observed streamflow data for 2010 year. Then the model was calibrated against the field measurements of water qualities, including BOD, T-N and T-P. In most cases, there were reasonable agreements between observed and predicted data. The validated model was used to analyze the characterization of pollutant load from study area. As a result, Non-point source pollutant loads during the rainy season was about 66~78% of total loads. In rainy-season, water quality parameters depended on precipitation and pollutant loads patterns, but their concentration were not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. As another result of evaluation for load duration curves, in order to improve water qualities to the satisfactory level, the watershed managements considering both time-variant and pollution sources must be required in the HRW. Overall, it was found that the model could be used conveniently to assess watershed characteristics and pollutant loads in watershed scale.