• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.621-635
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• 2020

Water quality models are scientific tools that simulate and interpret the relationship between physical, chemical and biological reactions to external pollutant loads in water systems. They are actively used as a key technology in environmental water management. With recent advances in computational power, water quality modeling technology has evolved into a coupled three-dimensional modeling of hydrodynamics, water quality, and ecological inputs. However, there is uncertainty in the simulated results due to the increasing model complexity, knowledge gaps in simulating complex aquatic ecosystem, and the distrust of stakeholders due to nontransparent modeling processes. These issues have become difficult obstacles for the practical use of water quality models in the water management decision process. The objectives of this paper were to review the theoretical background, needs, and development status of water quality modeling technology. Additionally, we present the potential future directions of water quality modeling technology as a scientific tool for national environmental water management. The main development directions can be summarized as follows: quantification of parameter sensitivities and model uncertainty, acquisition and use of high frequency and high resolution data based on IoT sensor technology, conjunctive use of mechanistic models and data-driven models, and securing transparency in the water quality modeling process. These advances in the field of water quality modeling warrant joint research with modeling experts, statisticians, and ecologists, combined with active communication between policy makers and stakeholders.

• Environmental Engineering Research
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• v.16 no.3
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• pp.113-119
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• 2011

This study traces the origin, evolution, and current state-of-the-art of engineering-oriented water-quality management and modeling. Three attributes of polluted water underlie human concerns for water quality: rubbish (aesthetic impairment), stink (ecosystem impairment), and death (public health impairment). The historical roots of both modern environmental engineering and water-quality modeling are traced to the late nineteenth and early twentieth centuries when European and American engineers worked to control and manage urban wastewater. The subsequent evolution of water-quality modeling can be divided into four stages related to dissolved oxygen (1925-1960), computerization (1960-1970), eutrophication (1970-1977) and toxic substances (1977-1990). Current efforts to integrate these stages into unified holistic frameworks are described. The role of water-quality management and modeling for developing economies is outlined.

• Environmental Engineering Research
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• v.14 no.4
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• pp.200-210
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• 2009

The modern era of water quality modeling in the United States began in the 1960s. Pushed by advances in computer technology as well as environmental sciences, water quality modeling evolved through five broad periods: (1) initial model development with mainframe computers (1960s - mid 1970s), (2) model refinement and generalization with minicomputers (mid 1970s - mid 1980s), (3) model standardization and support with microcomputers (mid 1980s - mid 1990s), (4) better model access and performance with faster desktop computers running Windows and local area networks linked to the Internet (mid 1990s - early 2000s), and (5) model integration and widespread use of the Internet (early 2000s - present). Improved computer technology continues to drive improvements in water quality models, including more detailed environmental analysis (spatially and temporally), better user interfaces and GIS software, more accessibility to environmental data from on-line repositories, and more robust modeling frameworks linking hydrodynamics, water quality, watershed and atmospheric models. Driven by regulatory needs and advancing technology, water quality modeling will continue to improve to better address more complicated water bodies and pollutant types, and more complicated management questions. This manuscript describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.4
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• pp.585-594
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• 2006

This study focused on the causes of fish kills and its prevention methods in Yudeung Stream, Daejeon, Korea. Intense field data, continuous water quality monitoring system and water quality modeling were applied to analyze the causes. Pollutant can be delivered to urban streams by surface runoff and combined sewer overflows in rainfall events. However, water quality analysis and water quality modeling results indicate that the abrupt fish kills in the Yudeung stream seems to be caused by combined effect of DO depletion, increase in turbidity and other toxic material. Excessive fish population in the study area may harm the aesthetic value of the stream and also has greater potential for massive fish kills. It is suggested to implement methods to reduce delivery of pollutants to the stream not only to prevent fish kills but also to keep balance of ecosystem including human uses. Frequent clean up of the urban surface and CSO, installation of detention basin will be helpful. In the long run, it seems combined sewer system has be replaced with separate sewer system for more effective pollutant removal in the urban area.

• Journal of environmental and Sanitary engineering
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• v.17 no.4
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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.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.13-22
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• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.427-430
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• 2006

Uncertainty is one of the key issues of the water quality management. Uncertainty occurs in the course of all water quality management stages including monitoring, modeling, and regulation enforcement. To reduce uncertainties of water quality monitoring, manualized monitoring methodology should be developed and implemented. In addition, long-term monitoring is essential for acquiring reliable water quality data which enables best water quality management. For the water quality management in the watershed scale, fate of pollutant including its generation, transport and impact should be considered while regarding each stage of water quality management as an unit process. Uncertainties of each stage of water quality management should be treated properly to prevent error propagation transferred to the next stage of management for successful achievement of water quality conservation.

• Journal of Environmental Impact Assessment
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• v.19 no.5
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• pp.465-473
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• 2010

This study was carried out to investigate the effect of EFDC hydrodynamic result on the WASP7.3 water quality modeling result in accordance with the change of number of grid for the dam reservoir to be constructed. The simulated flow and BOD, T-N and T-P loads by the HSPF watershed model was used for boundary conditions and the hydrodynamic modeling results was linked with WASP model to predict future water quality after dam construction. The scenarios for EFDC modeling were composed of Scenario 1(141 grid cells) and Scenario 2(568 grid cells). The results of Scenario 2 showed that BOD, T-N, T-P and Chl-a concentrations were decreased 0.073mg/L(8.5%), 0.032mg/L(2.6%), 0.003mg/L(6.8%), 0.644mg/L(4.2%) compared with those of Scenario 1, respectively. As number of grid cell increased, water quality concentrations were decreased and also it caused the longer running time. Therefore, this study suggests that the consideration of the geometry of water body is more important than the number of grid cells for the prediction of water quality of a dam reservoir in EIA.

• Journal of Environmental Health Sciences
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• v.24 no.1
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• pp.80-86
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• 1998

Seom River was major branch of Namhan river, consist of primary basin that Wonjoo-city, Hoingsung-gun and primary contamination source was sewage from human lives. This study was evaluated production contamination loading of each branch basin and water quality grade and water quality simulation by QUAL2E to provide efficient contaminations source control. Rusult of survey, production loading of BOD, T-N, T-P were 26,591 kg/day, 4,560 kg/day, 731 kg/day resectively. Water quality analysis in 17 points of main stream were appeared that 1st grade(BOD 1 mg/l under) was 6 point, 2nd grade was 9 point and 3rd grade was 2 point. And result of water quality analysis for branch steram, first grade was evaluated 68.7%. Based of field data, calibration and verification result were in good agreement with mesured value within coefficient of variance were from 2.59% to 18.73%, from 6.39%, to 28.46%, respectively.

• 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.