• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.353-366
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• 2018

The purpose of this study was assessment the quality of water by using the statistical analysis technique of the Water flow and water quality from January 2012 to December 2016 at the unit basin for total pollutant load management system (TPLMS) in the Imjin River. Water flow and water quality were monitored at an average of 8 day intervals, 11 parameters were used for correlation analysis, principal component analysis (PCA), factor analysis (FA), and cluster analysis (CA). The Hierarchical CA was classified into three according to the change of space, such as natural rivers, urban rivers, point with large influence of point pollution source, it was found that the type of contamination source the similarity of water quality affected the classification of cluster. Using one-way analysis of variance (ANOVA) and post-hoc Analysis, there were statistically significant differences between mean values among the clusters. Correlation analysis showed the correlation coefficient between $COD_{Mn}$ and TOC was 0.951 (p<0.01) and the correlation was statistically significantly higher. According to the result PCA and FA, 3 principal components can explaining 72% of the total variations in water quality characteristics and main factor was EC, $BOD_5$, $COD_{Mn}$, TN, TP and TOC indirect indicators of organic matter and nutrients were influenced. This study presented the regression equation obtained by applying the factor scores to the multiple linear regression analysis and concluded that the management Indirect indicators of organic matter and nutrients is important for water quality management in the Imjin River basin.

• Journal of Environmental Science International
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• v.18 no.2
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• pp.141-151
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• 2009

Temperature, salinity, COD, DIN (Dissolved Inorganic Nitrogen), DIP (Dissolved Inorganic Phosphorus), and Chlorophyll ${\alpha}$ obtained from the southern coastal waters during the period of 2003 to 2005 were analyzed. Variability in temperature was not found between groups in southern coastal waters, but significantly different depending on sampling sites (p<0.05). The average temperature in 2003 estimated at $18.33^{\circ}C$ that was annually increased by 2005 and significantly different based on statistics (p<0.05). Unlikely to temperature, salinity was significantly different depending on sampling sites, as well as monthly variations (p<0.05). Likewise to temperature, the value of salinity was annually increased. COD estimated at the average of $>1.7\;mg\;l^{-1}$ for three years, indicating optimal water quality. The fluctuations of nutrients were extremely shown in different sampling sites and monthly variations. Chlorophyll a recorded above $2.0{\mu}g\;l^{-1}$ which was associated with high primary phytoplankton, whereas it showed much fluctuations in temporal and spatial, In particular, Tongyong, Jaranman, Jinjuman, and Samcheonpo located in the southeast were the highest fluctuations in water quality than any other regions. The correlation between salinity/COD and nutrients/chlorophyll a was strongly negative or positive, which was possibly associated with much the introduction of run-off water as well as rainfall in summer.

• Journal of Korean Society on Water Environment
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• v.39 no.6
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• pp.451-464
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• 2023

Harmful cyanobacterial monitoring is time-consuming and requires skilled professionals. Recently, Phycocyanin, the accessory pigment unique to freshwater cyanobacteria, has been proposed as an indicator for the presence of cyanobacteria, with the advantage of rapid and simple measurement. The purpose of this research was to evaluate the correlation between the harmful cyanobacterial cell density and the concentration of phycocyanin and to consider how to use the real-time water quality monitoring system for algae bloom monitoring. In the downstream of the Nakdong River, Microcystis spp. showed maximum cell density (99 %) in harmful cyanobacteria (four target genera). A strong correlation between phycocyanin(measured in the laboratory) concentrations and harmful cyanobacterial cell density was observed (r = 0.90, p < 0.001), while a weaker relationship (r = 0.65, p < 0.001) resulted between chlorophyll a concentration and harmful cyanobacterial cell density. As a result of comparing the phycocyanin concentration (measured in submersible fluorescence sensor) and harmful cyanobacterial cell density, the error range increased as the number of cyanobacteria cells increased. Before opening the estuary bank, the diurnal variations of phycocyanin concentrations did not mix by depth, and in the case of the surface layer, a pattern of increase and decrease over time was shown. This study is the result of analysis when Microcystis spp. is dominant in downstream of Nakdong River in summer, therefore the correlation between the harmful cyanobacteria density and phycocyanin concentrations should be more generalized through spatio-temporal expansion.

• Journal of Soil and Groundwater Environment
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• v.29 no.3
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• pp.23-36
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• 2024

Miryang City, the study area, has a water supply rate of 87.4%, which is 12% lower than the national water supply rate of 99.4%, but has a high dependence on groundwater due to the high ratio of farms. In agricultural areas, contamination becomes relatively more critical, requiring significant attention to the management and conservation of groundwater resources. This study aims at estimate groundwater vulnerability of Miryang City using the DRASTIC index map, Piper diagram, and water quality data to correlated with the DRASTIC index. The results from DRASTIC map were divided into five classes: very high, high, moderate, low, and very low. The areas in central and southern part of study area, which are characterize by a very high index with [Ca-Cl] and [Na-Cl] water types, covering a large alluvium with the Miryang River and Nakdonggang River. In addition, a correlation analysis between groundwater quality parameters and the DRASTIC index was carried out. Chloride, sodium, and sulfate ions showed a weak relationship with DRASTIC index, with correlation coefficient was 0.507, 0.487 and 0.344, respectively. These results suggest that aquifer media, soil media, hydraulic conductivity, and chloride ion are important factors for groundwater vulnerability.

• Journal of Korean Society on Water Environment
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• v.35 no.2
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• pp.152-164
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• 2019

In this study, a Benthic Macroinvertebrates Family Index (BMFI) was developed using 100 indicator groups (99 families including Chironomidae with 2 phena). Families were assigned a score between 1 and 10 depending on their sensitivity to organic pollution. The BMFI was composed of the sensitivity and relative abundance of the indicator taxa. Sensitivity values of each group were generally similar to Biological Monitoring Working Party (BMWP) scores or Walley, Hawkes, Paisley, Trigg (WHPT) scores of UK, Japanese BMWP scores, and the FBI tolerance values of North America. However, sensitivity values of some taxa were significantly different from those of foreign countries, which seemed to have resulted from discrepancy in species composition, difference of taxonomic classification system, or methodological difference for estimation of sensitivity. As an annual average level, BMFI showed significant correlation with concentration of 5-day biochemical oxygen demand (BOD5) (correlation coefficient r = -0.80, n = 569 sites), total suspended solids (r = -0.68), and total phosphorus (r = -0.79). In addition, BMFI revealed strong correlation with Shannon-Weaver's species diversity (r = 0.85), Margalef's species richness (r = 0.85) and McNaughton's dominance (r = -0.84). Correlation between BMFI and water quality parameters or community indices such as species diversity did not show significant difference compared to that of species-level indices such as BMI (Benthic Macroinvertebrates Index). This means that BMFI is a more useful indicator in terms of easy identification of organisms. BMFI was used to assess the environmental status of 3,017 sites of Stream Ecosystem Survey conducted by the Korean Ministry of Environment between 2016 and 2018. As a result, about half of all sites appeared to be in good condition, and a quarter in poor condition.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.48-57
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• 2009

A two-dimensional (2D), laterally-averaged hydrodynamic and water quality model, CE-QUAL-W2 was applied to evaluate the performance on simulating the effect of flushing from Daecheong Reservoir on the downstream water quality variations during the flushing events held on November, 2003 and March, 2008. The hydraulic and water quality simulation results were compared with field measurement data, as well as a one-dimensional (1D), unsteady model (KORIV1) that revealed limited capability in the previous study due to missing the resuspension process of river bottom sediments. The results showed that although the 2D model made satisfactory performance in reproducing the temporal variations of dissolved matters including phosphate, ammonia and nitrate, it revealed poor performance in simulating the increase of biological oxygen demand and suspended sediment (SS) concentrations during the passage of the flushing flow. The reason of the error was that the resuspension process of the 2D model is only the function of shear stress induced by wind. In reality, however, as shown by significant correlation between bottom shear stress ($\tau$) and observed SS concentration, the resuspension process can be significantly influenced by current velocity in the riverine system, especially during flushing event. The results indicate that the resuspension of river bottom materials should be incorporated into the water quality modeling processes if $\tau$ is greater than a critical shear stress (${\tau}_c$) for better simulation of flushing effect.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.9-19
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• 2024

As using public monitoring data, analysing a trends of water quality change, establishing a criteria to determine abnormal status and constructing a regression model that can predict Chlorophyll-a, an indicator of eutrophication, was studied. Accordingly, the three freshwater lakes were selected, approximately 20 years of water quality monitoring data were analyzed for periodic changes in water quality each year using regression analysis, and a method for determining abnormalities was presented by the standard deviation at confidence level 95%. By calculating the temporal change rate of Chlorophyll-a from irregular observed data, analyzing correlations between the rate and other water quality items, and constructing regression models, a method to predict changes in Chlorophyll-a was presented. The results of this study are expected to contribute to freshwater lake water quality management as an approximate water quality prediction method using the statistical model.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1733-1741
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• 2020

This study analyzed the effect of meteorological factors on the concentration of PM10 (particulate matter 10) in the atmosphere and the variation of rainwater quality using multivariate statistical analysis. The concentration of PM10 in the atmosphere was continuously measured during eleven precipitation events with a custom-built PM sensor node. A total of 183 rainwater samples were analyzed for pH, EC (electrical conductivity), and water-soluble cations (Na+, Mg2+, K+, Ca2+, NH4+) and anions (Cl-, NO3-, SO42-). The data has been analyzed using two multivariate statistical techniques (principal component analysis, PCA, and Pearson correlation analysis) to identify relationships among PM10 concentrations in the atmosphere, meteorological factors, and rainwater quality factors. When the rainfall intensity was relatively strong (> 5 mm/h, rainfall type 1), the PM10 concentration in the atmosphere showed a negative correlation (r = -0.55, p < 0.05) with cumulative rainfall. The PM10 concentration increased the concentration of water-soluble ions (r = 0.25) and EC (r = 0.4), and decreased the pH (r = -0.7) of rainwater samples. However, for rainfall type 2 (< 5 mm/h), there was no negative correlation between the PM10 concentration in the atmosphere and cumulative rainfall and no statistically significant correlation between the PM10 concentration in the atmosphere and rainwater quality.

• Journal of Korean Society on Water Environment
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• v.40 no.2
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• pp.89-100
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• 2024

Climate change has a broad impact on the entire water environment, and this impact is growing. Climate adaptation in water supply systems often involves quantity and quality control, but there has been a lack of research examining the impacts of climatic factors on water supply productivity and operation conditions. Therefore, the present study focused on, first, building a database of climatic factors and water purification operating conditions, and then identifying the correlations between factors to reveal their impacts. News big data was analyzed with keywords of climatic factors and water supply systems in either nationwide or region-wide analyses. Metropolitan area exhibited more issues with cold waves whereas there were more issues with drought in the Southern Chungcheong area. A survey was conducted to seek experts' opinions on the climatic impacts leading to these effects. Pre-chlorination due to drought, high-turbidity of intake water due to rainfall, an increase of toxins in intake water due to heat waves, and low water temperature due to cold waves were expected. Pearson correlation analysis was conducted based on meteorological data and the operating data of a water purification plant. Heavy rain resulted in 13 days of high turbidity, and the subsequent low turbidity conditions required 3 days of high coagulant dosage. This insight is expected to help inform the design of operation manuals for waterworks in response to climate change.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.3
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• pp.137-144
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• 2015

The purpose of this study is to develop an warning system to detect real-time water quality abnormality using a multivariate statistical approach. In this study, we applied principal component analysis among multivariate data analyses which was used for the correlation between water quality parameters considering the real-time algorithm to determine abnormality in water quality. We applied our approach to real field data and showed the utilization of algorithm for the real-time monitoring to find water quality abnormality. In addition, our approach with Korea Meterological Adminstration database identified heavy rain data due to climate change is one of the most important factors to explain water quality abnormality.