• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1053-1060
• /
• 2021

Current water quality monitoring systems in Korea carried based on in-situ grab sample analysis. It is difficult to improve the current water quality monitoring system, i.e. shorter sampling period or increasing sampling points, because the current systems are both cost- and labor-intensive. One possible way to improve the current water quality monitoring system is to adopt a modeling approach. In this study, a modeling technique was introduced to support the current water quality monitoring system, and an artificial neural network model, the computational tool which mimics the biological processes of human brain, was applied to predict water quality of the river. The approach tried to predict concentrations of Total coliform at the outlet of the river and this showed, somewhat, poor estimations since concentrations of Total coliform were rapidly fluctuated. The approach, however, could forecast whether concentrations of Total coliform would exceed the water quality standard or not. As results, modeling approaches is expected to assist the current water quality monitoring system if the approach is applied to judge whether water quality factors could exceed the water quality standards or not and this would help proper water resource managements.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.4
• /
• pp.723-728
• /
• 2019

Citizens' distrust of water pollution is very high in tap water that we routinely drink. In addition, water pollution accidents of tap water are difficult to predict and the risk is high, so real-time monitoring and management are needed. Therefore, it is necessary to introduce real-time water quality monitoring using the Internet of things(IoT). Residual chlorine is more persistent and economical than other disinfectants and it is easy to check residual effect, so it is mainly used as a disinfection index in waterworks. It can be monitored in real time by using IoT technology in order to secure the safety of tap water. In this study, we developed smart device for real-time water quality monitoring using amperometry sensor and analyzed its performance.

• Journal of Environmental Science International
• /
• v.24 no.7
• /
• pp.907-915
• /
• 2015

The tap water is generally known to be corrosive in the pH range at 6.5 ~ 7.5. And the degree of corrosion varies depending on the types of raw water such as river surface water or lake water of the dam. Although several corrosion index represents the corrosivity of tap water, the typical corrosion indexes such as Langelier saturation index (LI) and calcium carbonate precipitation potential (CCPP) were calculated to monitoring the corrosive water quality about raw and tap water in water distribution system. To control the corrosive water quality, the correlation between corrosion index and water quality factors were examined. In this study, corrosion index (LI, CCPP) and the pH was found to be most highly correlated.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2002.10a
• /
• pp.401-404
• /
• 2002

Two irrigation districts, Maekok and Byungjum 1 which are irrigated with polluted stream flow, and one control district Kichun, that is supplied from a reservoir complying with the water quality standard are selected for water quality monitoring to identify the effects of polluted irrigation on crop yields, environments, and health hazards for farmers. The water quality at Maekok and Byungjum 1 districts are worse than the control district, and continuous water quality monitoring are needed for the wastewater reuse for agriculture.

• Journal of Korean Society on Water Environment
• /
• v.28 no.1
• /
• pp.18-25
• /
• 2012

For effective watershed management, it is very important to select the tributaries through selection and concentration of targeted tributary catchments for improving water quality within the limited financial conditions. This study introduced the selection and diagnosis procedure of tributary catchments for improving water quality at Chungcheongnam-do based on water quality and flowrate monitoring, stream grouping method. The tributaries with high value of water quality and flowrate were selected for improving water quality according to stream grouping method. The diagnosis of selected tributaries for improving water quality was performed with analysis of the pollution load (generated, discharged, delivered) and point source discharged pollution load density. The plans for improving water quality of tributaries were suggested thorough various diagnosis of tributary catchments. For improving water quality of tributaries in Chungcheongnam-do, the tributary catchments in the Dangjin, Asan, Yesan, Cheonan, Hongseong area should be preferentially considered. The water quality improving plans for those tributary catchments, in accordance with the reduction of sources of pollution by population and livestock, should be established.

• Journal of Korean Society of Environmental Engineers
• /
• v.34 no.2
• /
• pp.119-125
• /
• 2012

The tributary water quality and flowrate monitoring result, which is fundamental data for the establishment of the water environmental policy, is used as very important data for the implementation of TMDL. This study introduced how to use the tributary water quality and flowrate monitoring data for the analysis of the watersheds, the satisfactory assessment of water quality standards in the watersheds, the selection of watersheds for the establishment of the implementation plan, and the selection of the tributary catchments for improving the water quality using a stream grouping method. According to the analytical results of tributary catchment using water quality and flowrate monitoring data of thirty-seven tributaries in the Geum-River watershed at Chungcheongnam-do, the value of flowrate in the tributaries, which is located in the middle-lower Geum-River watershed, was greater than the other areas and the concentration of the water pollutants regardless of water quality parameters in the tributaries at Nonsancheon catchment was relatively higher than the other areas. The problems, which have the determination of satisfaction of water quality standards and selection of target watersheds for establishment of the implementation plan regardless of the water quality of tributary in the watershed due to the water quality and flowrate monitoring results of the main river, were improved use of the results of tributary water quality and flowrate monitoring. Also, the tributary catchments for improving the water quality, according to stream grouping method based on the results of tributary water quality and flowrate monitoring, were selected. In the Geum-River watershed at Chungcheongnam-do, the tributary in the Nonsancheon, Byeongcheoncheon, Seokseongcheon, Jocheon catchments, which has a large flow and a high concentration of water pollutants, should be preferentially selected for improving the water quality of the tributary in accordance with the reduction of the source of pollution.

• Journal of Internet of Things and Convergence
• /
• v.9 no.1
• /
• pp.41-47
• /
• 2023

Today, due to the increase in global population growth, the international community is discussing solving the food problem. The aquaculture industry is emerging as an alternative to solving the food problem. For the innovative growth of the aquaculture industry, smart fish farms that combine the fourth industrial technology are recently being distributed, and full-cycle digitalization is being promoted. Water quality sensors, which are important in the aquaculture industry, are electrochemical portable sensors that check water quality individually and intermittently, making it impossible to analyze and manage water quality in real time. Recently, optically-based monitoring sensors have been developed and applied, but the reliability of monitoring data cannot be guaranteed because the state information of the water quality sensor is unknown. Therefore, this paper proposes an algorithm representing self-diagnosis status such as Failure, Out of Specification, Maintenance Required, and Check Function based on monitoring data collected by water quality sensors to ensure data reliability.

• Journal of Korean Society on Water Environment
• /
• v.20 no.4
• /
• pp.321-326
• /
• 2004

The objective of this study is to test the applicability of neural network models to forecast water quality at Naesa and Pyongchang river. Water quality data devided into rainy day and non-rainy day to find characteristics of them. The mean and maximum data of rainy day show higher than those of non-rainy day. And discharge correlate with TOC at Pyongchang river. Neural network model is trained to the correlation of discharge with water quality. As a result, it is convinced that the proposed neural network model can apply to the analysis of real time water quality monitoring.

• Journal of Environmental Impact Assessment
• /
• v.29 no.1
• /
• pp.61-77
• /
• 2020

In South Korea, major public waters have been systematic management under national level. Water environment network has been continuous monitoring for change of aquatic ecosystem, river and reservoir. In Water Quality Monitoring Networks, the data have been generally monitored Per eight days or month, while in Automatic Water Quality Monitoring Network the data have been monitored at daily intervals. Therefore, we were compared and analyzed water quality data between the networks using statistic method for same water quality item. Mann-kendall test results confirm that all points in Water Temperature (WT) and DO were not statistically significant. In particular, the result revealed that there is significant variation of TOC in the four different sites, TN in two different sites, TP in three different sites, WT in seven different sites, pH in two different sites between Water Quality Monitoring Network and Automatic Water Quality Monitoring Network. As a result firm LOWESS, TOC and pH clearly shows different trend. Among different sites, the water quality show the significantly positive correlations between at Sinam-Sangju2 and Namgang-Namgang4. Negative correlation significantly appeared in TP (ADD_Lower-AD1 site), TOC (DG-SG site), pH (GR-GR site), TP (JP-CN) and TN, TP, pH, EC, DO (GC-GC2-1 site).

• Journal of Environmental Impact Assessment
• /
• v.4 no.3
• /
• pp.31-39
• /
• 1995

Environmental Impact Assessment (EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, alternative assessment, mitigation measures, and post management. Environmental monitoring data for air quality or water quality, etc. is applied in the EIA process, especially in prediction and post management. As an effective tool of environmental monitoring, the remote sensing method, introduced recently, was used in collecting nationwide data concerning ecosystem and land use. This article explains the current monitoring status in Korea. Monitoring factors include air quality, water quality, soil, ocean, odor, noise, and ecosystems. This report explains the organization of the environmental monitoring system managed by the Ministry of Environment in Korea. Furthermore, it shows the environmental criteria and environmental policies applied to EIA in Korea.