• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.463-474
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• 2002

A two-dimensional water quality management model, Unsteady/Uncertainty Water Quality Model(UUWQM), is developed for a hydrodynamic analysis, an advection-diffusion analysis, and a reliability analysis by using uncertainty technique. The model is applied to the 35 km reach of Sungju to Hyunpoong in the midstream of Nakdong River. 2-D hydrodynamic and water quality analyses are peformed in this reach. Important input variables are decided by sensitivity analysis and verified by Monte Carlo method. Frequency distributions of water quality concentrations are computed from MFOSM method and Monte Carlo method at several locations in this study area. A water quality management system is constructed by calculating the violation probabilities of existing water quality standards.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.578-583
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• 2000

In order to operate water quality model for a lake or a channel, user should examine the all kinds of parameters and should know how them react to the model for calculating the pollution which are happened from the watershed or are reacted in the water. The aim of this study is analyzing the characteristics of parameters which are used by a water quality model (CE-QUAL-W2), so that we are trying to find out how them to react to the model for calculating the many kinds of pollution.

• Journal of Environmental Science International
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• v.5 no.3
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• pp.377-385
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• 1996

This study aims at the estimation of a river management flow in urban basin analyzing Sinchun basin to be the tributary of Kumho river basin. The river management flow has to satisfy a low flow as natural flow and an environmental preservation flow estimated by a dilution flow to satisfy a target water quality in drought flow. Therefore for the estimation of a river management flow in Sinchun in this study, first Tank model as a basin runoff model estimates a low flow, a drought flow from a flow duration curve in Sinchun, second QUAL2E model as water quality model simulates water quality in Sinchun and estimates environmental preservation flow to satisfy a target water qua%its, BOD 8 mg/l by a dilution flow derived from Kumho river, Nakdong river and around water. And the river management flow is estimated by addition of a use flow and a loss flow to more flow between a low-flow and an environmental preservation flow.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.3
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• pp.253-261
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• 2001

Nowadays, various water quality prediction models have been studied, then these models can support the method which evaluate the effect of various alternative water quality management by simulation without experimentation. But, It is necessary to create complex input data file for applying these water quality model and even though the appropriate result is extracted, it is impossible to use as decision making data effectively because of the limitation of expression of model itself. As this study is about the stream water quality modeling, for overcoming the model's above limitation, by developing an interface which can calculate the pollutant load of watershed, I could create a input data file and visualize the simulation result so that I was going to integrate water quality model and GSIS using Flexible coupling applied to GSIS in the pre-process and post-process on model. The QUAL2E model, used in this study, is verified by stream water quality model in previous various results of study and has many examples through previous study, because that is appropriate to water quality model, especially in Korea, and comparatively accurate and their usage is quite simple.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.3
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• pp.112-123
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• 1997

The Anyang stream is one of the Han river in Seoul Metropolitan area. It is 35.1km long, has a basin area of $282.26km^2$ and touches seven cities of Kyounggido and some of Seoul Metropolitan area. The situations of Anyang stream have resulted in severe stream water pollution problems. The purpose of this study were to measure the hydraulic characteristics and water quality, to make the countermeasures to achieve the stream water quality, to suggest the future conditions to improve water quality trough the Hydrodynamic and Water Quality Modal(WASP4). As the result of Anyang stream water quality forecsat, they are follows. Sewerage systems in the watershed of the Anyang stream have to be amended for wrong systemn and constructed in the upstream area of Anyang. The discharge of industrial wastewater has to be throughly controlled from the upstream area of the Anyang stream. Hydrodynamic and Water Quality Model(WASP4) for this study revealed the future water quality of the Anyang stream by computer simulation.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.38-49
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• 2012

In this study, we analyze statistical characteristics of influent water quality in Daejeon waste water treatment plant and apply a stochastic model for data generation. In the analysis, the influent water quality data from year 2003 to 2008, except for year 2006, are used. Among water quality variables, we find strong correlations between BOD and T-N; T-N and T-P; BOD and T-P; $COD_{Mn}$ and T-P; and BOD and $COD_{Mn}$. We also find that different water quality variables follow different theoretical probability distribution functions, which also depends on whether the seasonal cycle is removed. Finally, we generate the influent water quality data using the multi-season 1st Markov model (Thomas-Fiering model). With model parameters calibrated for the period 2003~2005, the generated data for 2007~2008 are well compared with observed data showing good agreement in general. BOD and T-N are underestimated by the stochastic model. This is mainly due to the statistical difference in observed data itself between two periods of 2003~2005 and 2007~2008. Therefore, we expect the stochastic model can be applied with more confidence in the case that the data follows stationary pattern.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.710-718
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• 2011

An integrated water quality management of reservoir and river would be required when the quality of downstream river water is affected by the discharge of upstream dam. In particular, for the control of downstream turbidity during flood events, the integrated modeling of reservoir and river is effective approach. This work was aimed to develop a laterally-averaged two-dimensional hydrodynamic and water quality model (CE-QUAL-W2), by which water quality can be predicted in the downstream of Yongdam dam in conjunction with the reservoir model, and to validate the model under two different hydrological conditions; wet year (2005) and drought year (2010). The model results clearly showed that the simulated data regarding water elevation and suspended solid (SS) concentration are well corresponded with the measured data. In addition, the variation of SS concentration as a function of time was effectively simulated along the river stations with the developed model. Consequently, the developed model can be effectively applied for the integrated water quality management of Yongdam dam and downstream river.

• Journal of Environmental Impact Assessment
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• v.20 no.1
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• pp.25-36
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• 2011

In this study, the accurate water quality analysis in rivers, including the non-point source is performed. First of all, watershed model, SWAT(Soil and Water Assessment Tool) was applied to analyze the impact of the non-point source in study area. And then, water quality analysis integrating the point source and the non-point source is implemented using QUALKO model. For more exact simulation, it should be the calibration and verification of variables and parameters which are needed for simulation. In addition, the importance of considering the non-point source was confirmed in river water quality simulation. BOD, TN, TP were analysed, and the results shows that BOD, TN and TP concentration was increased to 16.8%, 8.2% and 25.8% respectively. The more accurate estimate will be carried if use of reliable measurements and watershed simulation be done in models linking process. The suggested technique will improve the accuracy of the water quality analysis. The methodologies presented in this study will contribute to basin-wide water quantity and quality management.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.359-366
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• 2012

Accurate predictions about the water quality of a river have great importance in identifying in-stream flow and water supply requirements and solving relevant environmental problems. In this study, the effect of water release from upstream dam on the downstream water quality has been investigated by applying a hydological model combined with QUAL2E to Geum River basin. The ESP (Ensemble Stream Prediction) method, which has been validated and verified by lots of researchers, was used to predict reservoir and tributary inflow. The input parameters for a combined model to predict both hydrological characteristics and water quality were identified and optimized. In order to verify the model performance, the simulated result at Gongju station, located at the downstream from Daecheong Dam, has been compared with measured data in 2008. As a result, it was found that the proposed model simulates well the values of BOD, T-N, and T-P with an acceptable reliability.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.6
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• pp.738-748
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• 2005

Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.