• Journal of Korea Water Resources Association
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• v.37 no.9
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• pp.719-727
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• 2004

Water quality models can be applied to manage the regional water quality problems and to estimate the target and allowable pollution load in watershed effectively. The optimization of state variables in the given water quality model Is necessary to build up more effective model. The least-squares method is applied to fit field observations in QUAL2E developed by U.S. EPA, which is most widely used one in the world to simulate the stream water quality, and the optimization model with constraints is constructed to estimate the parameters. The objective function of the optimization model is solved by Solver in Microsoft Excel and Monte Carlo simulation is conducted to know the influence of parameter in conventional pollutants. It is found that this technique is easily implemented and rapidly convergent computational procedure to calibrate the parameters after appling this approach in Anyang stream located in Kyonggi province mainly.

• Journal of Korean Society on Water Environment
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• v.22 no.1
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• pp.166-171
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• 2006

The objectives of the present paper were to investigate the concentration of total coliform in wastewater effluents and the effect of water chemical and physical characters in it. The most correlated parameter with total coliform was COD. It means that the wastewater treatment efficient effects on total coliform concentration. And we developed predictive model for the total coliform concentration. The estimated parameters for model were COD, temperature, nitrite, chloride, Mn and regression model equation was determined; log (Total Coli.) = 1.861+0.065[COD]+0.038[temperature]-0.0004[$Cl^-$]+3.697[Mn]-0.32 [$NO_2-N$] The developed model provided very strong correlation ($R^2:0.82$) between total coliform and regression equation. The parameters having high sensitivity were COD and temperature. So the study indicated that if the temperature and COD of wastewater effluent were known, we would estimate the concentration of total coliform and decide the most effective usage of chlorine.

• Journal of Korean Society on Water Environment
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• v.26 no.2
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• pp.332-342
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• 2010

A model has been developed to investigate in-river sediment and phosphorus dynamics. This advective-dispersive model is coupled with hydrodynamics and sediment transport submodels to simulate suspended sediment, total dissolved phosphorus, total phosphorus, and particulate phosphorus concentrations under unsteady flow conditions. It emphasizes sediment and phosphorus dynamics in unsteady flow conditions, in which the study differs from many previous solute transport studies, conducted in relatively steady flow conditions. The diffusion wave approaximation was employed for unsteady flow simulations. The first-order adsorption and linear adsorption isotherm model was used on the basis of the three-layered riverbed submodel with riverbed sediment exchange and erosion/deposition processes. Various numerical methods were tested to select a method that had minimal numerical dispersion under unsteady flow conditions. The responses of the model to the change of model parameter values were tested as well.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.856-864
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• 2006

For estimating the minimum discharge to maintain a river, low flow analysis is required and long term runoff records are needed for the analysis. However, runoff data should be estimated to run a hydrologic model for ungaged river basin. For the reason, parameter estimation is crucial to simulate rainfall-runoff events for those basins using Tank model. In this study, only runoff data recorded for dry season are used for parameter estimation, which is different to other methods based on runoff data recorded for wet and dry seasons. The Harmony Search algorithm is used to determine the optimum parameters for Tank model. The coefficient of determination ($R^2$) is served as the objective function in the Harmony Search. In cases that recorded data are insufficient, the recording interval is changed and Empirical CDF is adopted to analyze the estimated parameters. The suggested method is applied to Yongdam dam, Soyanggang dam, Chungju dam and Seomjingang dam basins. As results, the higher $R^2s$ are obtained when the shorter recording interval, the better recorded data quality, and the more rainfall events recorded along with certain rainfall amount is. Moreover, when the total rainfall is higher than the certain amount, $R^2$ is high. Considering the facts found from this study for the low flow analysis, it is possible to estimate the parameters for Tank model properly with the desired confidence level.

• Journal of Korea Water Resources Association
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• v.37 no.12
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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 Health Sciences
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• v.42 no.4
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• pp.280-292
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• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.1
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• pp.55-62
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• 2012

This study is to assess the reduction of nonpoint source pollution by applying Best Management Practice (BMP) in Chungju-dam watershed (6,585.1 $km^2$) using Soil and Water Assessment Tool (SWAT). The model was calibrated using 3 years (1998-2000) daily streamflow at 3 locations and monthly water quality of sediment (SS), total nitrogen (T-N) and total phosphorus (T-P) data at 2 locations and validated for another 3 years (2001-2003) data. The 5 BMPs of streambank stabilization, porous gully plugs, recharge structures, terrace, and contour farming were applied to stream and area with the specific criteria of previous researches. Through the parameter sensitivity analysis, the farming practice P-factor and Manning's roughness of stream were sensitive. Overall, the NPS reduction effect was high for streambank stabilization, terrace, and contour farming. At the watershed outlet, the SS, T-P, and T-N were reduced by 64.4 %, 62.8 % and 17.6 % respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.221-230
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• 1997

In hydrology analysis, the result of a slope analysis for terrain have an very important effect on water quality and water quantity Recently, a slope analysis tend to use the digital elevation model rater than the traditional map sheet. But a terrain slope analysis by the digital elevation model depends on grid size of the digital elevation model. Hence the effect of a slope analysis by the digital elevation model is a important factor. In this study, therefor, in order to determine a hydrological parameter and a terrain parameter for simulation of the water quality and the hydrological property, we adapted two sample area that are the Nerin stream of the basin of the Soyang lake and a Osip stream of Samchuk, and its individual coverages are $640\;km^2$ and $33\;km^2$. Also to analyze the effect of grid size in the slope of a basin, we apply DEM changing a grid size respectively at intervals of 100 m from 100 m to 1.000m for the Nerin stream basin and at intervals of 10 m from 20 m to 300 m for the Osip stream basin.

• Water Engineering Research
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• v.4 no.2
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• pp.59-68
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• 2003

The applicabilities and validities of two methodologies fur the prediction of THM (trihalomethane) formation in a water pipeline system were proposed and discussed. One is the multiple regression technique and the other is an artificial neural network technique. There are many factors which influence water quality, especially THMs formations in water pipeline systems. In this study, the prediction models of THM formation in water pipeline systems are developed based on the independent variables proposed by American Water Works Association(AWWA). Multiple linear/nonlinear regression models are estimated and three layer feed-forward artificial neural networks have been used to predict the THM formation in a water pipeline system. Input parameters of the models consist of organic compounds measured in water pipeline systems such as TOC, DOC and UV254. Also, the reaction time to each measuring site along pipeline is used as input parameter calculated by a hydraulic analysis. Using these variables as model parameters, four models are developed. And the predicted results from the four developed models are compared statistically to the measured THMs data set. It is shown that the artificial neural network approaches are much superior to the conventional regression approaches and that the developed models by neural network can be used more efficiently and reproduce more accurately the THMs formation in water pipeline systems, than the conventional regression methods proposed by AWWA.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.547-551
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• 1998

Reaeration coefficient is the physical absorption of oxygen from the atmosphere by water. It is the most important natural means by which a stream replaces the oxygen consumed in the biodegradation of organic wastes, and the rate constant describing this process is the reaeration coefficient, It. Reaeration coefficient is the dominant parameter affecting the use of water quality model. Therefore accurate estimation of the reaeration coefficient is essential for optimum water quality management. There is several method to estimate stream reaeration coefficient. In this study, it would be concluded that SI-peak method is of practical use when applied to small stream, and CRI method is adequate to large stream.