scholarly journals Water Quality Assessment and Potential Source Contribution Using Multivariate Statistical Techniques in Jinwi River Watershed, South Korea

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 2976
Author(s):  
Hyeonmi Choi ◽  
Yong-Chul Cho ◽  
Sang-Hun Kim ◽  
Soon-Ju Yu ◽  
Young-Seuk Kim ◽  
...  
Keyword(s):  
Water Quality ◽  
Unit Area ◽  
Pollution Sources ◽  
Quality Data ◽  
Water Quality Parameter ◽  
Pollution Level ◽  
Multivariate Statistical ◽  
Rapid Urbanization ◽  
Pollutant Load ◽  
River Watershed

To investigate the effects of rapid urbanization on water pollution, the water quality, daily unit area pollutant load, water quality score, and real-time water quality index for the Jinwi River watershed were assessed. The contribution of known pollution sources was identified using multivariate statistical analysis and absolute principal component score-multiple linear regression. The water quality data were collected during the dry and wet seasons to compare the pollution characteristics with varying precipitation levels and flow rates. The highest level of urbanization is present in the upstream areas of the Hwangguji and Osan Streams. Most of the water quality parameter values were the highest in the downstream areas after the polluted rivers merged. The results showed a dilution effect with a lower pollution level in the wet season. Conversely, the daily unit area pollutant load was higher in the rainy season, indicating that the pollutants increased as the flow rate increased. A cluster analysis identified that the downstream water quality parameters are quite different from the upstream values. Upstream is an urban area with relatively high organic matter and nutrient loads. The upstream sewage treatment facilities were the main pollution sources. This study provides basic data for policymakers in urban water quality management.

scholarly journals Assessment of Nakdong River Basin Management: Target Water Quality Achievement and Future Challenges

2020 ◽  
Vol 20 (2) ◽  
pp. 251-263
Author(s):  
Kyeong Hwan Kang ◽  
Junghyeon Kim ◽  
Hyeonjin Jeon ◽  
Kyoungwoo Kim ◽  
Imgyu Byun
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Water Environment ◽  
Quality Data ◽  
Master Plan ◽  
Nakdong River ◽  
Environment Management ◽  
Pollutant Load ◽  
Nakdong River Basin ◽  
Representative Points

In 2006, the Korean Ministry of Environment established <The 1st Water Environment Management Master Plan>. The plan aimed at “Clean Water, Eco River 2015” and guided water quality protection and strengthened water management. This study evaluated the achievement of the target water quality among the 33 mid-level basins in the Nakdong River basin and assessments of the causes of non-achievement of the target water quality by mid-level basins. According to the 2015 water quality data, only 16 of the 33 mid-level basins achieved the target water quality. The low achievement of the target water quality was attributed to the failure to predict the pollutant load at the time of planning, problems with the management of tributaries, implementation of the <Four major river restoration project>, and problems with the representativeness of the water quality representative points. In addition, feasibility studies on the water quality monitoring representative point used in each mid-level basin were also performed; some mid-level basins required improvement or change of the representative points. This study also suggested further research to improve water quality, such as detailed studies of the management of pollutant load, mainstream tributaries, and water quality indicators, for the revision of the current ongoing <The 2nd Water Environment Management Master Plan>.

A GIS-Based Spatial-Multivariate Statistical Analysis of Water Quality Data in the Porsuk River, Turkey

2009 ◽  
Vol 44 (3) ◽  
pp. 279-293 ◽  
Author(s):  
Ozan Arslan
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Quality Assessment ◽  
Statistical Methods ◽  
Multivariate Statistical Analysis ◽  
Water Quality Assessment ◽  
Quality Data ◽  
Multivariate Statistical ◽  
Water Quality Data ◽  
Porsuk River

Abstract The study offers a GIS-based multivariate statistical analysis strategy to assess river water quality. Multivariate statistical methods and Geographic Information System (GIS) technology have effectively been used for water quality management. Recognizing the fact that the use of standard statistical methods can be restrictive due to the complexity of water quality datasets, geospatial statistical methods have been recommended for the water quality assessment. The objective of the study was to explore the potential capabilities of GIS-based joint multivariate statistical analysis for water quality assessment of Porsuk River in Turkey. A well-known multivariate statistical technique, principal component analysis (PCA), is incorporated into a geographic database for interpretation of water quality data. To characterize spatial variability of water quality data, spatial PCA was performed on the basis of spatial autocorrelation. Application of the joint spatio-multivariate statistical analysis for interpretation of the water quality database offered a better understanding of the hydrochemistry in the study region.

The water quality and pollution sources assessment of Surma river, Bangladesh using, hydrochemical, multivariate statistical and water quality index methods

2021 ◽  
Vol 12 ◽  
pp. 100523
Author(s):  
M. Farhad Howladar ◽  
Elora Chakma ◽  
Nusrat Jahan Koley ◽  
Sabina Islam ◽  
Md Abdullah Al Numanbakth ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Quality Index ◽  
Pollution Sources ◽  
Multivariate Statistical ◽  
Index Methods ◽  
Surma River
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