• Membrane and Water Treatment
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• v.10 no.1
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• pp.1-11
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• 2019

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.363-370
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• 1999

Remotely sensed data is regarded as a potentially effective data source for the measurement of water quality and for the environmental change of water bodies. In this study, we measured the spectral reflectance by using multi-spectral image of low resolution camera(LRC) which will be loaded in the OSMI multi-purpose satellite(KOMPSAT) scheduled to be launched on 1999 to use the data in analyzing water pollution. We also investigated the possibility of extraction of water quality factors in water bodies by using remotely sensed low resolution data such as NOAA/AVHRR. In this study, Shiwha-District and Sang-Sam Lake was set up as the subject areas for the study. In this part of the study, we measured the spectral reflectance of the water surface to analyze the radiance of the water bodies in low resolution spectral band and tried to analyze the water quality factors in water bodies by using radiance feature from another remotely sensed data such as NOAA/AVHRR. As the method of this study, first, we measured the spectral reflectance of the water surface by using SFOV( Single Field of View) to measure the reflectance of water quality analysis from every channel in LRC spectral band(0.4~O.9${\mu}{\textrm}{m}$). Second, we investigated the usefulness of ground truth data and the LRC data by measuring every spectral reflectance of water quality factors. Third, we analyzed water quality factors by using the radiance feature from another remotely sensed data such as NOAA/AVHRR. We carried out ratio process of what we selected Chlorophyll-a and suspended sediments as the first factors of the water quality. The results of the analysis are below. First, the amount of pollutants of Shiwha-Lake has been increasing every you since 1987 by factors of eutrophication. Second, as a result of the reflectance, Chlorophyll-a represented high spectral reflectance mainly around 0.52${\mu}{\textrm}{m}$ of green spectral band, and turbidity represented high spectral reflectance at 0.57${\mu}{\textrm}{m}$. But suspended sediments absorbed high at 0.8${\mu}{\textrm}{m}$. Third, Chlorophyll-a and suspended sediments could have a distribution chart as a result of the water quality analysis by using NOAA/AVHRR data.

• Journal of Korean Society on Water Environment
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• v.23 no.2
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• pp.260-265
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• 2007

This study was carried out to complement water quality standards and to establish new concept for water quality standards reflecting current state of water quality in small streams. By this purpose, discriminant analysis was performed and Water Quality Level Model (WQLM) was developed using the data such as EC, BOD, $COD_{Mn}$, SS, T-N, T-P, $NH_3-N$ in 224 agricultural streams. To give water quality level for water quality parameters, it divided into 20% respectively in the order of excellent water quality. On the basis of the lowest water quality level, water quality level of small streams is granted. As a result of it, number of stream corresponding to Level I was no, Level II was 2 streams, Level III was 22 streams, Level IV was 70 streams, and Level V was 130 streams. Average of water quality in each level was the highest in Level V. EC, SS, and T-N of 7 parameters were selected in variance concerned water quality level. By standardized canonical discriminant function coefficient, EC of three variances was the highest in 0.625 at the discriminant power. The next was T-N (0.509), SS (0.414). By discriminant function for water quality level, Level II was equal to $-2.973+19.376{\times}(EC)+0.647{\times}(T-N)+0.009{\times}(SS)$, Level III was equal to $-3.288+19.190{\times}(EC)+0.733{\times}(T-N)+0.041{\times}(SS)$, Level IV was equal to $-4.462+27.097{\times}(EC)+0.792{\times}(T-N)+0.053{\times}(SS)$, and Level V was equal to $-9.117+40.040{\times}(EC)+1.305{\times}(T-N)+0.111{\times}(SS)$. As a result of test at real agricultural watershed of Jeongan and Euidang in Gongju city, the fitness of WQLM was high to 88.78%. But, to get accomplished water quality assessment more exactly in agricultural streams, we had to concentrate and get vast data, and WQLM was modified and complemented continually.

• 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 Korea Water Resources Association
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• v.35 no.2
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• pp.149-159
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• 2002

The monthly water quality data measured at 19 stations located in the Sapkyo reservoir watershed were clustered into 2 to 7 clusters and factor analysis was conducted to characterize the water quality, using the information obtained from cluster analysis. The result of cluster analysis shows that Sapkyo reservoir and each stream (Sapkyo stream, Muhan stream and Kokkyo stream) in Sapkyo reservoir watershed hove their own water quality characteristics. The result of water quality analysis indicates that the concentration of suspended solids from Sapkyo reservoir is much higher than those of other streams, and which is probably because of increment of phytoplankton biomass with rich nutrient flowing Into Sapkyo reservoir from the upper stream of watershed. Furthermore, the concentrations of biochemical oxygen demand and chemical oxygen demand were 3.5 to 4.8 times and 1.7 to 2.5 times those of other streams, respectively. The overall water quality of Sapkyo reservoir watershed was considered to exceed eutrophic condition. Based on factor analysis, the water quality characteristics of Sapkyo stream and Muhan stream were closely related with farm land and residence. The water quality of Kokkyo stream was influenced by superabundant organic matter flowing from Chonan city and district wastewater treatment plant located in the upper stream of Kokkyo stream. The water quality factor influencing Sapkyo reservoir was closely related with water quality factors of other three streams.

• Journal of Korean Society of Water and Wastewater
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• v.31 no.1
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• pp.83-91
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• 2017

This study analyzed the correlation between Chl-a and water quality factors using characteristics of climate data, water quality factors, and various statistical analysis techniques during the summer season in the Nakdong River during the 2-year period. The purpose of this study is to provide the basic data for establishing water quality management policy in the Changnyeong-Haman weir section. From the end of July to the middle of August when algae mainly occur, both the years 2015 and 2016 are in the temperature range of $25{\sim}30^{\circ}C$, and the total precipitation of 2015 is less than that of 2016 in this period. As a result of comparing the concentration of Chl-a, the average Chl-a concentration of 2015 was higher than that of 2016, which seems to be related to the total precipitation in the occurrence of algae. The results of the correlation analysis showed that the correlation with PO4-P was significant at most points. As a result of the factor analysis, the first principal factor group classified PO4-P, NH3-N, TP, pH, flow rate, TN and this section seems to be influenced by phosphorus and nitrogen and flow rate.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.119-127
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• 2014

The objective of this study is to evaluate and analyze Sumjin River Basin water environment system. It was necessary to improve the water quality. The data were collected from 2010 January to 2012 December including Water Temperature, pH, DO, EC, $BOD_5$, COD, TOC, SS, T-N, T-P. The data were used to study were required to; Correlation Analysis; Principle Component Analysis; Factor Analysis. The results were as followed. According to correlation analysis on $BOD_5$ against COD, TOC it revealed that the each value of correlation coefficient were 0.715 and 0.719; this means the strength of the relationship is strong. The same analysis on T-P against $BOD_5$, COD, TOC, SS has revealed that the range of the correlation coefficient value fell between 0.482 and 0.608 which means strength of the relationship between them remained normal. Through correlation analysis, it has been found that all elements except T-N have high correlation. The results of principal component analysis to target the overall water quality was extracted to three main components. The cumulative contribution rate is 68.990%. In the case of seasonal water quality, Spring and Summer are extracted to each of four main components. The cumulative contribution rate is 81.515% and 73.550% respectively. Fall and Winter are extracted to each of three main components. The cumulative contribution rate is 65.072% and 72.721% respectively. There is no seasonality in the case of factor analysis. The first common factor is $BOD_5$, COD, TOC, SS, T-P, which were classified. Totally speaking, Sumjin River Basin water system gets highly affected by the nutrient salts, organic matter and suspended solid at the same time.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.606-614
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• 2009

To evaluate the biological water quality, diatom-based biological indices (DAIpo and TDI) were examined in the Sum-River and the Dal-stream. Having BOD concentrations below $2mg{\cdot}L^{-1}$ in most sites, water quality of both rivers was good. The DAIpo and TDI values ranged from 29.8 to 91.4 and from 38.7 to 93.0 respectively. From the biological water quality assessment, DAIpo and TDI for both rivers displayed fair to fairly poor water quality levels. However, the two indices showed more polluted conditions than expected from the BOD vlaues. In addition, DAIpo, having wider range of differences, appears to be more sensitive to the change in water quality when compared to TDI values. Statistical analysis using principal component analysis showed that Nitzschia palea and Diatoma vulgare might not be the appropriate indicators due to their low correlations with other indicators.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.143-148
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• 2006

There are need to manage the water quality to supply an safety to consumer through pipe and reservoir the drinking water that produced in a clean water reservoir. However, a management of water quality and monitoring in reservoir have never been performed. Recently, the government has enforced standards of water quality. However, we have a inferior technology of water quality as compared with one in USA, Japan, Germany, etc. In case of water quality inspection and analysis equipments, sensor technology is very important to improve the water quality inspection and to develop the analysis equipments. In this paper, we analyze a law and a regulation for management of drinking water quality, and propose the measurement standards of drinking water quality in pH, conductivity, residual chloride, turbidity and water temperature. Then, we analyze electrode sensors that interference within pH, conductivity, residual chloride in interference experiment.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.136-144
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• 2018

The Ministry of the Environment conducts a water environment management plan and TMDL(Total Maximum Daily Load) for integrated watershed management, and determines whether the target water quality is achieved using water quality monitoring data. The concentration of monitoring points located in the downstream of the watershed is the outcome of complicated mechanisms such as influx of pollutants from the tributaries of the watershed and self-purification of river water. The purpose of this study is to analyze the effect of main stream and tributary water quality on the target water quality point using the water pollution source tracking and exceedance rate of watershed. In this study, FDC and exceedance rate analysis were performed on six water quality items including BOD and T-P, which are the targets of TMDL. Water quality items and points affecting the target water quality point were derived from flow rate. In this study, the pollution source tracking through FDC analysis and exceedance rate analysis will be able to establish more efficiently the water quality management strategy for each branch to achieve the target water quality.