• Journal of Korean Society of Water and Wastewater
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• v.14 no.2
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• pp.181-195
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• 2000

The effect of the intercepting ratios on the water quality improvement was simulated by using Finite Segment Method in a urban river where intercepting sewer under the ground and constructing sewage treatment plant are now being proceeded. To simulate variations of the water quality caused by river flows, rating curve at each gaging station was derived from measurements. Water quality data were from the exiting observations at each key stations from 1990 to 1998, for 1999 and 2000 data we measured in creek and drainage ditch in addition to observation stations. It revealed that increasing the intercepting ratios improved the water quality.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.63-69
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• 1999

The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.

• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.67-75
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• 2004

In this study, real-time forecasting model(Neural Dam Inflow Forecasting Model; NDIFM) based on neural network to predict the dam inflow which is occurred by flood runoff is developed and applied to check its availability for the operation of multi-purpose reservoir Developed model Is applied to predict the flood Inflow on dam Nam-Gang in Nak-dong river basin where the rate of flood control dependent on reservoir operation is high. The input data for this model are average rainfall data composed of mean areal rainfall of upstream basin from dam location, observed inflow data, and predicted inflow data. As a result of the simulation for flood inflow forecasting, it is found that NDIFM-I is the best predictive model for real-time operation. In addition, the results of forecasting used on NDIFM-II and NDIFM-III are not bad and these models showed wide range of applicability for real-time forecasting. Consequently, if the quality of observed hydrological data is improved, it is expected that the neural network model which is black-box model can be utilized for real-time flood forecasting rather than conceptual models of which physical parameter is complex.

• Journal of Environmental Health Sciences
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• v.28 no.3
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• pp.19-25
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• 2002

In this paper, the water quality forecast was performed on the BOD of the Chungju Dam using the ARIMA model, which is a nonlinear statistics model, and the artificial neural network model. The monthly data of water quality were collected from 1991 to 2000. The most appropriate ARIMA model for Chungju dam was found to be the multiplicative seasonal ARIMA(1,0,1)(1,0,1)$_{12}$, model. While the artificial neural network model, which is used relatively often in recent days, forecasts new data by the strength of a learned matrix like human neurons. The BOD values were forecasted using the back-propagation algorithm of multi-layer perceptrons in this paper. Artificial neural network model was com- posed of two hidden layers and the node number of each hidden layer was designed fifteen. It was demonstrated that the ARIMA model was more appropriate in terms of changes around the overall average, but the artificial neural net-work model was more appropriate in terms of reflecting the minimum and the maximum values.s.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.609-617
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• 2007

The goal of this study is to forecast the trend of stream quality and to suggest some policy alternatives in Gumbo river. It used the five different monthly time series data such as BOD, COD, T-N and EC of the nine of Gumbo River measurement points from Jan. 1998 to Dec. 2006. Water pollution is serious at Gumbo2 and Palgeo stream measurement points. BOD, COD, T-N and EC data are analyzed with the exponential smoothing model and the trend is forecasted until Dec. 2009.

• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.485-494
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• 2005

It is very important to analyze the correlation between discharge and water quality. The observation of discharge and water quality are effective at same point as well as same time for real time management. But no less significant is the fact that there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. In this case, it need to observe accurate discharge data, and to develop forecasting program or system using real time data. In this paper, discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and compared with discharge using WMS(Watershed Modeling System) model. WMS shows better results when peak discharge is small and hydrograph is smooth. Forecasted discharge of neural network model have achieved the highest overall accuracy of specific discharge and WMS. Neural network model forecast change of discharge well on unrecored station.

• Journal of Environmental Science International
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• v.19 no.1
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• pp.39-45
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• 2010

When the Juam multipurpose dam which is connected with existing large water supply facilities is finished, water environment is changed from stream to lake. The changed quality of water should be examined. In this study, the result of water quality forecasting is analysed and an effective management plan of water quality is presented. Tn this study, the WASPS model that is a dynamic water quality simulation model was selected to forecast the water quality. This model forecasts movement of change of pollutants. For an application of the model, the subject areas were divided into seventeen sub-areas by considering change temperature depending measuring points and on depth of water. Meteorological data collected by the meteorological observatory and data about quality measured by the Korea Water Resources Development Corporation were used for an operation of the model. As a result of quality examination through quality data and estimated pollutant loading, the water quality environment criterion was grade II and the nutritive condition was measured as meso-graphic grade. In this study, an effective management was planned to improve water quality by reducing pollution load. According to the result of examination, when more than 30% of BOD was reduced it was recorded that the environment standard of water quality was improved to the second grade.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.71-80
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• 2005

Recently, water quality problems are emerging as important social issues since water quality in rivers and lakes are significantly deteriorated. Thus, an accurate prediction system on reservoir water quality is required, as well as an integrated system which can provide a solution for taking away contaminated materials. This research aims to develop an intelligent decision support system, which uses a GIS enabling management and spatial analysis. The developed system is a prototype that can be applied into real spot. This research area includes the following main subjects; system analysis and design, geometry data collection and database implementation, data acquisition and analysis on reservoir water quality, interface design and development GIS, and development of an expert system for water quality forecasting by WASPS.

• Journal of Korean Society on Water Environment
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• v.32 no.6
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• pp.570-581
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• 2016

A watershed model was constructed using the Hydrological Simulation Program Fortran to predict the water quality, especially chlorophyll-a concentraion, at major tributaries of the Nakdong River basin, Korea. The BOD export loads for each land use in HSPF model were estimated at $1.47{\sim}8.64kg/km^2/day$; these values were similar to the domestic monitoring export loads. The T-N and T-P export loads were estimated at $0.618{\sim}3.942kg/km^2/day$ and $0.047{\sim}0.246kg/km^2/day$, slightly less than the domestic monitoring data but within the range of foreign literature values. The model was calibrated at major tributaries for a three-year period (2008 to 2010). The deviation values ranged from -31.5~1.6% of chlorophyll-a, -24.0~2.2% of T-N, and -5.7~34.8% of T-P. The root mean square error (RMSE) ranged from 4.3~44.4 ug/L for chlorophyll-a, -0.6~1.5 mg/L for T-N, and 0.04~0.18 mg/L for T-P, which indicates good calibration results. The operational water quality forecasting results for chlorophyll-a presented in this study were in good agreement with measured data and had an accuracy similar with model calibration results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.123-130
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• 1992

The quantity point has been considered prior to the quality point in the water resources development and management. However, the quality problems have become as important as quantity problems due to the industrialization and civilization. This paper presents a methodology of the integrated management of multiple reservoir systems by considering both water quantity and quality problems. It also presents a long-term forecasting technique of reservoir water quality by using the developed phosphorous model. The methodology was applied to the Han river reservoirs operation, in which five major reservoirs were considered. The result shows that the spatially and temporally distributed water quantity and quality resources can be utilized by meeting all the required constraints.