• Journal of Korean Society of Water and Wastewater
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• 제25권3호
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• pp.349-357
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• 2011

This study has an objective to estimate effect on water-quality enhancement by removal of contaminated river-bed material using a two-dimensional numerical modeling in the Seonakdong River, the Pyunggang River and the Maekdo River. RMA2 and RMA4 models were used for flow and contaminant transport simulation, respectively. After the analysis of the effects of flow restoration plan for the Seonakdong River system made by Lee et al (2008), simulation have been performed about scenarios which contains operations of the Daejeo Gate, the Noksan Gate, the Makdo Gate (on planning), and the Noksan Pumping Station. Because there is no option for elution from bed sediment in the RMA4 model, a simple technique has been used for initial condition modification for elution. The analyses revealed that the effect on water quality improvement due to dredging of bed sediment seemed to be less than 10 % of the total effect. The most efficient measure for the water quality improvement of the river system was the linked operation of water-gates and pumping station.

• Journal of Environmental Science International
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• 제9권6호
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Journal of Environmental Impact Assessment
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• 제3권2호
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• pp.25-32
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• 1994

This study was carried out as the Anyang creek water quality management using Geographic Information System (GIS) is the purpose of this pilot project to apply a GIS to environmental management field. Analysis of water quality data has been investigated using GIS with modeling of water quality management for the Anyang creek. The results of this study are summarized as follows: 1. The concentration of Mercury in sediment was increased rapidly nearby A26(Nightsoil Treatment Plant) and maximum was showed at A18 (Imgok bridge). Cadmium was increased rapidly at A35(Chulsan bridge). 2. River water quality management using visible computer system as GIS is effective to make decision for water quality management plan and database of environmental factors should be completed before applying GIS. 3. When water pollution accident is occurred in the river water system, pollutant source can be traced and analysed systematically using GIS to manage pollutants discharged into the river water system.

• Journal of Korean Society on Water Environment
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• 제28권1호
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• pp.84-93
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• 2012

The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.

• Journal of Korean Society on Water Environment
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• 제21권6호
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• pp.609-616
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• 2005

A high ammonia nitrogen ($NH_3-N$) concentration has been recursively observed every winter season in Geum River, which hindered chemical treatment processes at a water treatment plant. A flushing discharge from Daecheong Dam was often considered to dilute $NH_3-N$, but information on the quantitative effect of flushing on the downstream water quality was limited. In this study, the impact of a short-term reservoir flushing on the downstream water quality was investigated through field experiments and unsteady water quality modeling. On November 22, 2003, the reservoir discharge was increased from $30m^3/sec$ to $200m^3/sec$ within 6 hours for the purpose of the experiment. The results showed that flushing flow tends to reduce downstream $NH_3-N$ concentrations considerably, but the effectiveness was limited by flushing amount and time. An unsteady river water quality model was applied to simulate the changes of nitrogen concentrations in response to reservoir flushing. The model showed very good performance in predicting the travel time of flushing flow and the effect of flushing discharge on the reduction of downstream $NH_3-N$ concentrations at Maepo and Geumnam site, but a significant discrepancy was observed at Gongju site.

• Journal of Korea Water Resources Association
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• 제37권12호
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• pp.1009-1018
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• 2004

A systematic method using an optimal estimation algorithm is presented for simultaneous estimation of diffuse pollution distributed along a stream reach and model parameters for a stream water quality model. It was applied with the QVAL2E model to the South Han River for optimal estimation of kinetic constants and diffuse loads along the river. Initial calibration results for kinetic constants selected from a sensitivity analysis reveal that diffuse source inputs for nitrogen and phosphorus are essential to satisfy the system mass balance. Diffuse loads for total nitrogen and total phosphorus were estimated solving the expanded inverse problem. Comparison of kinetic constants estimated simultaneously with diffuse sources to those estimated without diffuse loads, suggests that diffuse sources must be included in the optimization not only for its own estimation but also for adequate estimation of the model parameters. Application of optimization method to river water quality modeling is discussed in terms of the sensitivity coefficient matrix structure.

• Journal of environmental and Sanitary engineering
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• 제17권4호
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• pp.1-9
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• 2002

In order to define about concern with discharge and water-quality, it is calculated drought flow, low flow, normal flow and wet flow in Chungju watershed from flow duration analysis. Water quality modeling study is performed for forecasting at upstream of Chungju lake. It is devided method of modeling into before and after the equipment of environmental treatment institution. And it is estimated the change of water quality. Before the equipment of environmental treatment, BOD concentration is increased from 23000 to 2006 years at all site and decrease on 2012 years. The rate of increasing BOD concentration is showed height between 2000 years and 2003 years most of all site. And after the equipment of environmental treatment, it is showed first grade of BOD water quality in most of sample site beside Jucheon river. The result of water quality modeling using drought flow showed that a lot of pollution occurred. And water quality using wet flow is good, so much discharge make more improve water quality than little discharge.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 1993년도 수공학연구발표회논문집
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• pp.125-132
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• 1993

• Journal of Korean Society of Water and Wastewater
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• 제22권1호
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• pp.121-129
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• 2008

Major factors affecting water quality in rivers are transportation, input of pollutant loads and kinetic transformation of pollutants. Government level decision makings on water quality management are based on steady state water quality modeling. However, it is more than often that such a steady state assumption is far from real situations in rivers. Therefore, it is unavoidable to have modeling errors in water quality modeling especially for steady state modeling for longer period of time. Authors attempted to identify sources of errors in results of steady state models and thus tried to find out ways to minimize those errors. Three water quality models, QUAL2E (Brown et al., 1983), QUAL2K (Chapra et al., 2006) and CAP (Seo and Lee, 2000) were applied to the lower stream of the Geum River. $BOD_5$ and COD tend to underestimate observed data while TN and TP showed relatively smaller errors. QUAL2E model provided best calibration results for BOD5 and TP and QUAL2K model showed best calibration results for TN. Since these errors are only relative values, it was difficult to conclude which model is better performing in certain situations. The most probable reasons for errors in water quality modeling are; 1) inappropriate consideration on flow characteristics, 2) lack of information on incoming pollutant load and 3) inappropriate location of sampling for water quality analysis.

• Journal of Korean Society on Water Environment
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• 제29권2호
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• pp.212-222
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• 2013

A watershed model was constructed using Hydrological Simulation Program Fortran to quantitatively predict the stream flows at major tributaries of Nakdong River basin, Korea. The entire basin was divided into 32 segments to effectively account for spatial variations in meteorological data and land segment parameter values of each tributary. The model was calibrated at ten tributaries including main stream of the river for a three-year period (2008 to 2010). The deviation values (Dv) of runoff volumes for operational stream flow forecasting for a six month period (2012.1.2 to 2012.6.29) at the ten tributaries ranged from -38.1 to 23.6%, which is on average 7.8% higher than those of runoff volumes for model calibration (-12.5 to 8.2%). The increased prediction errors were mainly from the uncertainties of numerical weather prediction modeling; nevertheless the stream flow forecasting results presented in this study were in a good agreement with the measured data.