• Journal of Korean Society on Water Environment
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• v.34 no.2
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• pp.202-209
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• 2018

The purpose of this study was to analyze the correlation between the effluent of a sewage treatment plant (STP) and the adjacent stream located downstream of the STP in Nakdong River. Flow and water quality data, such as BOD, COD, SS, T-N, and T-P data, for 12 STPs and adjacent downstream monitoring stations in the main stream and tributaries of Nakdong River were collected from 2012 to 2015. As a result of correlation analysis between river flow and water quality at the river water quality measurement point, COD, SS, and T-P were correlated positively with the river flow rate at 6, 8, and 6 points, respectively. As a result of analyzing the water quality of sewage treatment plant effluents and downstream streams, BOD and COD were correlated at 2 and 3 points, respectively. T-N showed a positive correlation at 9 points, and 7 of them had a strong positive correlation, indicating that sewage treatment effluent had a large effect on downstream streams. In this study, we found that the correlation between the river flow rate and the water quality factors (COD, SS, TP) was high at river water measurement points, and the sewage treatment plant effluent was correlated with the T-N value of adjacent streams.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.36-36
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• 2012

Drainage water in lowland paddy fields is quantitatively influenced recycle and/or repeated irrigation by irrigation facilities, i.e. pumps, check gates, small reservoirs and so on. In those drainage channels, nutrients accumulation and increasing organic matters are considered to be occurred, and water quality would be degraded not only environmental aspect but irrigation purpose. In general, Total Nitrogen (T-N) is interested water quality index in irrigation water, because high nitrogen concentration sometimes caused decreasing rice production by excess growth and fallen or degrading quality of taste, then, farmers would like to clear water less than 1mg/L of T-N concentration. In drainage channel, it is known that the nitrogen concentration change is influenced by physical, chemical and biological properties, i.e, stream or river bed condition, water temperature, other water quality index, and plant cover condition. In this study, discharge data (velocity and level) in a drainage channel was monitored by an Acoustic Doppler system and water quality was sampled at same time in 2011. So those data was analyzed by multi regression model to realize hydrological and environmental factors to influence with nitrogen concentration. The results showed the difference tendency between irrigation and non-irrigation period, and those influenced factors would be considered in water quality model developing in future.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.493-493
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• 2018

The purpose of this study was to analyze the correlation between the effluent of the sewage treatment plant (STP) and the adjacent stream located downstream of the STP in Nakdong River. The flow and water quality such as BOD, COD, SS, T-N, and T-P data for 12 STPs and adjacent downstream monitoring stations in the main stream and tributaries of Nakdong River were collected from 2012 to 2015. As a result of correlation analysis between river flow and water quality at the river water quality measurement point, COD, SS and T-P were correlated positively with river flow rate at 6, 8, and 6 points, respectively. As a result of analyzing the water quality of sewage treatment plant effluent and downstream stream, BOD and COD were correlated at 2 and 3 points, respectively. T-N showed a positive correlation at 9 points, and 7 of them had a strong positive correlation, indicating that sewage treatment effluent had a large effect on downstream streams. In this study, we found that the correlation between river flow rate and water quality factors (COD, SS, TP) was high for river water measurement points, and the sewage treatment plant effluent was correlated with the T-N value of adjacent streams.

• Journal of Korean Society on Water Environment
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• v.29 no.4
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• pp.514-522
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• 2013

The major 24 tributaries in Nam-River mid-watershed were monitored for discharge and water quality in order to understand the characteristics of the watershed and to select the tributary catchment for improving water quality. According to the analytical results of discharge and water quality monitoring data of 24 tributaries, the mean value of discharge below $0.1m^3/s$ was 62.5% among the monitored tributaries and it mostly exceeded the water quality standards of Nam-river mid-watershed ($BOD_5$ = 3 mg/L, T-P = 0.1 mg/L over). According to the stream grouping method and the water quality delivery load density ($kg/day/km^2$) based on the results of tributary discharge and water quality monitoring, the tributary watersheds for improving the water quality were selected. In the Nam-River mid-watershed, tributaries in the GaJwaCheon, HaChonCheon catchment (Group D, $BOD_5$ = 3 mg/L over) and in the UirYeongCheon, SeokGyoCheon catchment (Group A, T-P = 0.1 mg/L over), which have a small flow (and/or large flow) and a high concentrations of water pollutants. The various water quality improving scheme for tributaries, in accordance with the reduction of potential point source pollution by living sewage and livestock wastewater, should be established and implemented.

• Environmental Analysis Health and Toxicology
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• v.6 no.3_4
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• pp.155-161
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• 1991

The water quality in Wonju stream, Seom river in Kangwon province and Bokha, Shindun stream in Kyeonggi province was investigated between the season of irrigation on July, 1990 and of non-irrigation on September in 1989. The results of water quality obtained from this study were as follows; As for water quality of the Wonju stream and the Seom river, the concentration of COD, T-N, SS and Cu, and for the Bokha, Shindun stream, the concentration of T-N, SS and Cu were exceeded standard levels of quality guideline of agricultural water use in the season of irrigation. However, in the water quality of Wonju and Bokha stream, the concentration of T-N , SS and Cu, and in the Seom river, the concentration of T-N, SS, Cu and Zn were exceeded standard levels of agricultural water quality in the season of non-irrigation. And the average water quality of the 4 streams were not suitable for agricultural water use. The comparison of the annual average water quality of the 4 streams for pH, DO, T-N and SS were in statistics significantly different with p values less than 0.01. When the average water quality between the season of irrigation and non-irrigation in each stream was compared, DO and COD in the Wonju stream, COD in the Seom river, pH, DO, T-N, SS and Cu in the Shindun stream showed a significant difference with p<0.01. The average in the sediment were; COD, 5.65∼26.53 ppm; Cu, 0.26∼0.49 ppm and Zn 0.95∼2.97 ppm. The concentration of three contaminants were markedly higher than the water quality. And the concentration of COD, Zn in the sediment showed a significant difference with p<0.01, and Cu showed a considerably significant difference with p<0.05.

• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.705-716
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• 2011

For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.225-233
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• 1998

It is necessary to check the water quality of the lake on a continuous basis to determine the appearance of water pollution; however, it not only takes much time and expenses but it is considerably difficult to investigate the wide range of the area. If we use the remote sensing technique through the use of satellites, the status of water quality can be checked covering many wide areas simultaneously; and because the same area can be measured on a periodic basis, it is extremely effective in investigating the water quality. Furthermore, as some of the Landsat sensors carry characteristics which sense objects according to wave length, the distribution of water quality can be checked relatively accurately within a short period of time, while its image can be displayed in color. Hence, this research has attempted to extract water quality elements, such as transparency, water depth, and surface water temperature by utilizing the satellite data, and has prepared the water quality distribution image map of the Lake Hwajinpo by presenting the related empirical formula of the water quality elements. If the water quality distribution image map is prepared after extracting the water quality elements from the DN of the Landsat TM image and then carrying out TIN analysis through the use of GIS, relatively more accurate pattern can be learned covering a wide rage of area than the pattern presented based on the value obtained from actual observation.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.46-60
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• 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

• Journal of environmental and Sanitary engineering
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• v.15 no.1
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• pp.88-94
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• 2000

The purpose of this study was to analyze and compare the contents of minerals and ionic components in domestic commercial natural mineral waters, and to investigate the relationship between water quality and characteristics of suspended and rocks there of its source. All mineral waters tested in this study met the korean mineral water quality guideline, although chemical components varied widely depending upon the geological characteristics and degree of urbanization of the source area or physical water treatment method. The water quality of commercial bottled water was different from that of source water, especially in cationic components, and showed a tendency to become worse with time elapsed. The water quality on the bottle was also different from the measured quality.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.437-440
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• 2002

By the explosive increase of population and industrialization the security of water resources is required, and water resource pollution problem is emerging as a serious social issue. For the ongoing Saemankeum project, lots of efforts are being put together to manage the water quality of the Saemankeum above a certain level, and it is sure that water quality management problem of main inflows from Mankyung River and Dongjin River is very important. Based upon the water quality data of Mankyung River this report examines its correlative characteristics by water quality sampling point factors and the water pollution resource factors, and subjects to provide elementary data for efficient water quality management of Mankyung River.