• Journal of Environmental Impact Assessment
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• v.3 no.2
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• pp.25-32
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• 1994

This study was carried out as the Anyang creek water quality management using Geographic Information System (GIS) is the purpose of this pilot project to apply a GIS to environmental management field. Analysis of water quality data has been investigated using GIS with modeling of water quality management for the Anyang creek. The results of this study are summarized as follows: 1. The concentration of Mercury in sediment was increased rapidly nearby A26(Nightsoil Treatment Plant) and maximum was showed at A18 (Imgok bridge). Cadmium was increased rapidly at A35(Chulsan bridge). 2. River water quality management using visible computer system as GIS is effective to make decision for water quality management plan and database of environmental factors should be completed before applying GIS. 3. When water pollution accident is occurred in the river water system, pollutant source can be traced and analysed systematically using GIS to manage pollutants discharged into the river water system.

• 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 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.

• 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 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.

• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.42 no.5
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• pp.103-113
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• 2000

A decision support system DSS-WQMRA (Decision Support System-Water Quality Management in Rural Area) was developed to help regional planners for the water quality management in a rural basin. The integrated model DSS-WQMRA, written in JAVA, includes four subsystems such as a GIS, a database, water quality simulation models and a decision model. In the system, the GIS deals with landuse and the location of pollutant sources. The database manages each data and supplies input data for various water quality simulation models. the water quality simulation model is composed of the GWLF( Generalized Watershed Loading Function), PCLM(Pollutant Loading Calculation Module) and the WASP5 model. The decision model based on mixed integer programming is designed to determine optimal costs and thus allow the selection of managemental practices to meet the water quality criteria. The methodology was tested with an example application in the Bokha River Basin, Kyunggi Province in Korea. It was proved that the integrated model DSS-WQMRA could be very useful for water quality management including the non-point source pollution in rural areas.

• 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 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 on Water Environment
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• v.29 no.5
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• pp.630-640
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• 2013

It is one of the most critical steps identifying impaired waterbodies exactly in the selection of target water quality indicators for the management of Total Maximum Daily Loads (TMDLs). Excess ratio and excess level were applied and analyzed by the stream zone basis in order to evaluate water impairment for Nakdong, Geum, Youngsan and Seomjin rivers. Each river basin was divided into stream zones in the light of its watershed and waterbody characteristics. Selected water quality parameters discussed in this study were pH, DO, BOD, COD, SS, T-P, T-Coli and F-Coli. The excess ratios of the water quality parameters were used to discriminate water bodies that did not meet water quality standards. The excess levels were used to classify the degradation of water quality. The excess ratios and the excess levels to the water quality criteria of the medium influence areas were used for each stream zone. The results indicate that the excess ratios and the excess levels are varied on the stream zone in each river basin. Three parameters, pH, DO and SS, met water quality standards in all stream zones. The other five parameters indicated very high excess ratios in most waterbodies, and especially T-P and T-Coli revealed to be very high excess levels in some waterbodies. These parameters could be considered as major target indicators for the management of TMDLs.