• Journal of environmental and Sanitary engineering
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• v.18 no.4
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• pp.6-14
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• 2003

A spring water quality was depend on the aquifer soil status. However, water quality was rapidly contaminated by artificial affects. In the contaminate components, the heavy metals were significantly important because the heavy metals influence the plants and the animals. But, it is difficult to find out how the heavy metal can affect in the water quality. According to the group analysis and the factor analysis, water quality management was advanced. The experimental area was divided into three region and six factor. The six factor could not define the overall water quality, however this method were one of the useful methods.

• Water Engineering Research
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• v.3 no.2
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• pp.143-153
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• 2002

As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.320-331
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• 2012

A combination system of catch canal and constructed wetland was designed and suggested to improve water quality in gagricultural region of lower Dong-jin river basin. In order to evaluate an water quality improvement efficiency of the designed combination system, the NPS-WET model was applied in this study. Simulation result of the NPS-WET shown that the nutrient load removal rate of constructed wetland was BOD, T-N, T-P and SS was 30.7~39.0%, 46~60%, 40.7~57.0% and 68.2~74.7%, respectively. Nutrients reduction of constructed wetland was higher in growing season than winter season because vital activity of microorganism, macrophyte and algae was augmented with high air and water temperature. Effluents from constructed wetland can affect water-quality of catch canal drains, especially, water-quality on junction point to Dong-jin river. Water-quality improvement in low-flowed catch canal (Un-san) was more significant than in high-flowed catch canal (Won-pyeong). In conclusion, a feasible design of constructed wetland is necessary to treat large quantity of receiving water. The NPS-WET is useful tool for assessing water-quality improvement efficiency using constructed wetland.

• Journal of Korean Society on Water Environment
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• v.22 no.6
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• pp.1045-1051
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• 2006

Geumgang canal is planned to connect Geumgang lake with Saemangeum lake to accelerate desalinization and dilute polluted water to improve water quality in Saemangeum lake. The purpose of this study is to evaluate the impact of water quality on Geumgang lake by diversion of its lake flow to Saemangeum lake. WASP5 model was used to estimate water quality of Geumgang lake. Model calibration and verification were done for water quality data for 2001 and 2002. Water quality concentrations in Geumgang lake were simulated for 4 scenarios, which were considered whether the Geumgang canal is built or not. As a result of simulations, there was little impact on water quality in Geumgang lake, though a little of the Geumgang lake flow diverted to Saemangeum lake. As the Geumgang canal is planned to divert the Geumgang water flow which were discharged into the sea through sluice gates when canal is not built, it is thought that there will be little change by diversion of water flow.

• Journal of Korean Society on Water Environment
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• v.29 no.6
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• pp.842-846
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• 2013

In 2012, the Korean Ministry of Environment (MOE) added 3 new water quality standards for the protection of human health; specifically, regarding 1,4-dioxane, formaldehyde, and hexachlorobenzene. In this study, we assimilated the water quality standards of these 3 substances from other countries, with respect to surface water quality standards for human health protection and drinking water standards. We subsequently investigated how these standard values were derived. 1,4-Dioxane is managed as an environmental standard for human health in Japan, and as a drinking water quality standard in WHO, New Zealand, and Japan with respect to both carcinogenic and non-carcinogenic effects. In New York, the oncogenic effects of formaldehyde in drinking water intake is considered, whereas WHO, Australia, New Zealand, and Japan also assess the non-carcinogenic effects of formaldehyde when setting their standards. USEPA and New York have a water quality standard for human health protection with respect to hexachlorobenzene based on carcinogenic effects. This study focuses on deriving water quality standards for the 3 new substances, or obtaining baseline information to revise the values of existing substances in the future.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.4
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• pp.453-460
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• 2004

The objective of this research is to develop the water quality management model to achieve the water quality goal and the minimization of the waste load abatement cost. Most of existing water quality management model can calculate BOD and DO. In addition to those variables, N and P are included in the management model of this study. With a genetic algorithm, calculation results from the mathematical water quality model can be used directly in this management model. Developed management model using genetic algorithm was applicated for the Youngsan River basin. To verify the management model, water quality and pollution source of the Youngsan River had been investigated. Treatment types and optimum treatment costs of the existing and planned WWTPs in the baisn were calculated from the model. The results of genetic algorithm indicate that Kwangju and Naju WWTP have to do the advanced treatment to achieve the water quality goal about BOD, DO and TP. Total annual treatment cost including the upgrade cost of existing WWTPs in the Youngsan River basin was about 50.3 billion Won.

• Journal of Wetlands Research
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• v.7 no.1
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• pp.81-91
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• 2005

We construct the hydrology-water quality monitoring system which can watch the variations of river flow and water quality in real time. We also construct the river management system through the hydrology-water quality monitoring system that can observe water quality and its variations for preparing for the accident of river pollution. The Gyecheon basin which is located at the upstream of Heoengseong dam is selected as an experimental watershed for the system construction. The real time monitoring system for getting more correct hydrological and water quality data consists of 3-rainfall gauge station, 3-water level gauge station, and 1-water quality gauge station. We intend that the data such as rainfall, water level, velocity, flow, and water quality will be collected and we try that the data may be used for practical and other purposes.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.1
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• pp.91-102
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• 2006

Most projects of tideland reclamation with dike construction produce estuarine reservoirs, which may result in water quality problems due to blocking of natural flow of stream water to the sea. External loadings to the reservoirs through tributaries are major concerns in a concerned water quality management. The water quality of a reservoir is greatly influenced by watershed drainage, and accurate estimation of pollutant is indispensable for in the reservoir management. Concentrations of the microorganisms in stream water and conventional parameters were monitored in the 13 water quality monitoring sites located in a rural watershed of Hwaong estuarine reservoir. The indicator of microorganisms showed strong correlation between them, and regression equations with $R^2\geq0.70$ may be used fur estimating one from other microorganisms. The relationships between water quality parameters obtained in this study may be used to infer one unknown pollutant concentrations from the measured pollutant loadings. This methodology could be applied to other areas where the watershed characteristics are not significantly different from the study area. High concentrations of nitrogen was observed in water quality monitoring sites affected by urban land uses and numbers of livestock in wet day as well as dry day, due to the influent of diffuse sources.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.1
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• pp.99-105
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• 2004

The present agricultural water quality standards are set by a policy goal. This is intended for water quality management of public water resources, but not for the use of water resources. These standards were not determined by considering the influence of water quality on the safety of agricultural produce and the growth, yield and quality of agricultural crops. Thus, this study was carried out to investigate the influence of irrigation water quality on the growth, yield, and grain quality of rice and acquire fundamental knowledges to set up irrigation water quality standards. The pot experiment was conducted with 4 treatments using irrigation waters with various total nitrogen concentrations (control, 1, 5, 10, 20mg/L) and replicated four times with randomized block design. The results of this study showed that plant height, number of tiller, plant dry weight, the uptake of N, P, and K, and rice protein contents tended to increase as the T-N concentration in irrigation water was increased. In addition, grain yield at T-N 20 mg/L was significantly higher than in the control, but the percentage of head rice was slightly lower due to the increase of green kernel and white belly/core kernel.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.