• 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.

• KCID journal
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• v.7 no.1
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• pp.19-26
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• 2000

The irrigation water supply and water quality from a pumping station were surveyed. Guiseok pumping station was selected as a monitoring site. Water level in irrigation canal was monitored continuously and water samples were taken and analyzed, periodical

• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.680-688
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• 2017

Water quality monitoring for flow rates and BOD/COD/T-N/T-P/SS/TOC concentrations has been conducted in Nakdong river tributaries since 2011. In this study concentrations and loading rates of BOD, T-P, and TOC were analyzed to evaluate water quality monitoring stations using accumulated data at 206 tributary monitoring stations in Nakdong river 2012 ~ 2016. Average concentration ranges for 206 monitoring stations were 0.3 ~ 6.4 mg/L, 0.025 ~ 1.562 mg/L, and 0.6 ~ 10.7 mg/L for BOD, T-P, and TOC, respectively. Additionally, average loading rate ranges were 0.96 ~ 46,040 kg/d, 0.087 ~ 1,834 kg/d, and 1.51 ~ 80,425 kg/d for BOD, T-P, and TOC, respectively. Average concentration for BOD, T-P, and TOC at each monitoring station was evaluated using ambient water quality standards of rivers and water quality regulation level for medium-sized management areas. Average loading rate and specific loading rate (loading rate/drainage basin area) for BOD, T-P, and TOC at each monitoring station was considered to evaluate monitoring stations using suggested classification (BOD, TOC: -1, 1 ~ 10, 10 ~ 100, 100 ~ 1,000, and 1,000 ~ kg/d; T-P: -0.1. 0.1 ~ 1, 1 ~ 10, 10 ~ 100, and 100 ~ kg/d) Using results of this study, various water quality status maps were provided, and three evaluation methods were suggested to determine priority monitoring stations in Nakdong river for rational water quality control and tributaries basin management.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.697-704
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• 2007

This study proposes an integrated technique of Genetic Algorishim (GA) and Geographic Information System (GIS) for designing the water quality monitoring networks. To develop solution scheme of the integrated system, fitness functions are defined by the linear combination of five criteria which stand for the operation objectives of water quality monitoring stations. The criteria include representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness level is obtained through calculations of the fitness functions and input data from GIS. To find the most appropriate parameters for the problems, the sensitivity analysis is performed for four parameters such as number of generations, population sizes, probability of crossover, and probability of mutation. Using the parameters resulted from the sensitivity analysis, the developed system proposed 110 water quality monitoring stations in the Nakdong River. This study demonstrates that the integrated technique of GA and GIS can be utilized as a decision supporting tool in optimized design for a water quality monitoring network.

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1661-1671
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• 2016

Water quality in Nakdong river was analyzed using 699 monitoring data sets including flow rates and water quality concentrations collected at 195 tributary monitoring stations (the priority management areas: 35 stations, the non-priority management areas: 160 stations) in 2015. The highest average concentrations of all data for BOD, COD, T-N, T-P, SS, and TOC were 30~600 times higher than the lowest concentrations while the highest average loading rates were 800,000~2,700,000 times higher than the lowest loading rates. Because of the very large differences in the concentrations and loading rates, the variation of the concentrations and loading rates in a priority management monitoring station for BOD, T-P, and TOC was analyzed using the coefficient of variation, the ratio of the standard deviation value to the mean value. For BOD, T-P, and TOC, the coefficients of variation for concentration were mostly less than 100%, whereas the coefficients of variation for loading rate ranged from 31.1% to 232.2%. The very big difference in the loading rates was due to the large variation in flow rates. As a result of this, the estimation of water quality at each monitoring station using the average values of the concentrations and loading rates might be not rational in terms of their representativeness. In this study, new water quality analysis methods using all collected monitoring data were suggested and applied according to the water quality standard in medium-sized management areas.

• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.700-706
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• 2010

Along the 4 major rivers in korea, there are automatic water quality monitoring (AWQM) stations to immediately respond to any pollution incident. Real-time data (temperature, DO, pH, EC and TOC) collected at each station were statistically treated to exclude outliers and keep valid data using Dixon's test and Discordance test. These applied methods were compared in terms of the number of the outliers sorted out. There was no significant difference between these methods. On the other hand, more outliers were sorted out from EC and TOC data, comparing with other water quality items. EC data did not show partly any variation for a long time at H station. If measured signal does not exceed ${\pm}0.001mS/cm$ from the sectional mean, the signal should be treated as normal data. Therefore, another routine was added to the data screening system, some data which were removed as outlier were restored.

• Journal of Soil and Groundwater Environment
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• v.16 no.3
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• pp.38-47
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• 2011

Groundwater monitoring data from the National Groundwater Monitoring Stations, a total of 320 stations, were analyzed to identify the response of water level and quality to the Odaesan earthquake (M4.9) occurred in January 2007. Among the total of eight stations responded to the earthquake, five wells showed water-level decline, and in three wells, water level rose. In terms of recovery, water levels in four stations had recovered to the original level in five days, but not in the rest four wells. The magnitude of water-level change shows weak relations to the distance between the earthquake epicenter and the groundwater monitoring station. However, the relations to the transmissivities of monitored aquifer in the station with the groundwater change were not significant. To implement the earthquake monitoring system through the groundwater monitoring network, we still need to accumulate the long-term monitoring data and geostatistically analyze those with hydrogeological and tectonic factors.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.46-52
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• 2012

The rapid water pollution in stream, river, lake and sea in recent years raises an urgent need for continuous monitoring and policymaking to conserve the global clean environment. In particular, the increasing water pollution in coastal marine areas adds to the importance of the environmental monitoring systems. In this paper, the mobile server is designed to gathers information of the water quality at coastal areas. The obtained data by the server is transmitted from field servers to the base station via multi-hop communication in wireless sensor network. The information collected includes dissolved oxygen(DO), hydrogen ion exponent(pH), temperature, etc. By the information provided the real-time monitoring of water quality at the coastal marine area. In addition, wireless sensor network-based flooding routing protocol was designed and used to transfer the measured water quality information efficiently. Telosb sensor node is programmed using nesC language in TinyOS platform for small scale wireless sensor network monitoring from a remote server.

• Korean Journal of Ecology and Environment
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• v.41 no.4
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• pp.423-430
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• 2008

As of September 2008,45 Automatic Water Quality Monitoring Systems (AWQMS) have been installed at different sites on the 4 rivers to detect early the presence of pollutants in water and to issue an alarm. We count the number of issuing alarms by AWQMS, however, we will find the alarm has hardly been issued. The reasons for the scarcity of alarm issue are extensively being examined. The National Institute of Environmental Research attributes wrong alarm criteria for each AWQMS station to one the reasons. In this study, a suggestion has been made to modify the current alarm criteria to correspond with characteristics of river water quality. The current system with only two criteria (low and high) should be replaced as four-criteria systems (low, medium, high, and severe) based on cases of other advanced countries and stream conditions of Korea. The highest value of data collected for 5 years was suggested as the alarm criteria for each parameter. Meanwhile the alarm criteria for VOCs, phenol and heavy metals were established as same as drinking water quality criteria.

• Advances in environmental research
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• v.7 no.2
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• pp.87-107
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• 2018

Water quality monitoring network needs periodic evaluations based on environmental demands and financial constraints. We used a genetic algorithm to optimize the existing water quality monitoring stations on the Sefid-Rud River, which is located in the North of Iran. Our objective was to optimize the existing stations for drinking and irrigation purposes, separately. The technique includes two stages called data preparation and the optimization. On the data preparation stage, first the basin was divided into four sections and each section was consisted of some stations. Then, the score of each station was computed using the data provided by the water Research Institute of the Ministry of energy. After that, we applied a weighting method by providing questionnaires to ask the experts to define the significance of each parameter. In the next step, according to the scores, stations were prioritized cumulatively. Finally, the genetic algorithm was applied to identify the best combination. The results indicated that out of 21 existing monitoring stations, 14 stations should remain in the network for both irrigation and drinking purposes. The results also had a good compliance with the previous studies which used dynamic programming as the optimization technique.