Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran)
Different methods and indicators are employed to determine water quality. In this study, to assess the quality of the international Aras River, 16 parameters were analyzed at 19 stations with seasonal data collected over two years (2020 and 2021), and multivariate statistical analysis methods, inclu...
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Razi University
2024-11-01
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| Series: | Journal of Applied Research in Water and Wastewater |
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| Online Access: | https://arww.razi.ac.ir/article_3437_a6155a3a07a6e0a5cbae2ac37276d7d0.pdf |
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| author | Mohammad Mostafa Shabarang Ebrahim Fataei Ali Akbar Imani Hooman Bahmanpour Mohammed Shabani |
| author_facet | Mohammad Mostafa Shabarang Ebrahim Fataei Ali Akbar Imani Hooman Bahmanpour Mohammed Shabani |
| author_sort | Mohammad Mostafa Shabarang |
| collection | DOAJ |
| description | Different methods and indicators are employed to determine water quality. In this study, to assess the quality of the international Aras River, 16 parameters were analyzed at 19 stations with seasonal data collected over two years (2020 and 2021), and multivariate statistical analysis methods, including cluster analysis and factor analysis, were utilized. The cluster analysis results categorized the studied stations into four clusters based on quality. The primary parameters influencing the grouping of water quality at the stations were BOD, COD, and T. Coli in the first cluster; T. Coli and NO3 in the second cluster; TDS, EC, and Turbidity in the third cluster; and BOD, COD, TDS, EC, and Turb. in the fourth cluster, respectively. The principal component analysis and factor analysis results indicated that the first two components explained 86% of the total variance. In the first component, with an eigenvalue of 5.94, the most influential parameters in the qualitative classification of the stations included pH, DO, EC, T. Coli, NO3, and Hg. In the second component, with an eigenvalue of 2.72, the parameters BOD, COD, Turb., and As played the most significant role in creating quality differences among the stations. Therefore, based on the obtained results, it was revealed that the reason for qualitative changes at different stations is due to the entry of human pollutants from various urban, industrial, mining, and agricultural sources as well as erosion in the river basin. Therefore, given the high precision of the analytical methods used in the evaluation of the qualitative aspects of the studied river’s water, it can be acknowledged that multivariable methods such as cluster analysis and factor analysis, can confidently determine the water quality of rivers and significant parameters affecting their quality and identify pollutants in the management of river water quality. |
| format | Article |
| id | doaj-art-b0fbe1f0dcf242aeacc7cf713a973218 |
| institution | Kabale University |
| issn | 2476-6283 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Razi University |
| record_format | Article |
| series | Journal of Applied Research in Water and Wastewater |
| spelling | doaj-art-b0fbe1f0dcf242aeacc7cf713a9732182025-01-18T11:37:21ZengRazi UniversityJournal of Applied Research in Water and Wastewater2476-62832024-11-0111214315010.22126/arww.2025.10788.13373437 Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran)Mohammad Mostafa Shabarang0Ebrahim Fataei1Ali Akbar Imani2Hooman Bahmanpour3Mohammed Shabani4Department of Environment, Ardabil Branch, Islamic Azad University, Ardabil, Iran.Department of Environment, Ardabil Branch, Islamic Azad University, Ardabil, Iran.Department of Agriculture, Ardabil Branch, Islamic Azad University, Ardabil, Iran.Department of Environment, Shahrood Branch, Islamic Azad University, Shahrood, Iran.Department of Water Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran.Different methods and indicators are employed to determine water quality. In this study, to assess the quality of the international Aras River, 16 parameters were analyzed at 19 stations with seasonal data collected over two years (2020 and 2021), and multivariate statistical analysis methods, including cluster analysis and factor analysis, were utilized. The cluster analysis results categorized the studied stations into four clusters based on quality. The primary parameters influencing the grouping of water quality at the stations were BOD, COD, and T. Coli in the first cluster; T. Coli and NO3 in the second cluster; TDS, EC, and Turbidity in the third cluster; and BOD, COD, TDS, EC, and Turb. in the fourth cluster, respectively. The principal component analysis and factor analysis results indicated that the first two components explained 86% of the total variance. In the first component, with an eigenvalue of 5.94, the most influential parameters in the qualitative classification of the stations included pH, DO, EC, T. Coli, NO3, and Hg. In the second component, with an eigenvalue of 2.72, the parameters BOD, COD, Turb., and As played the most significant role in creating quality differences among the stations. Therefore, based on the obtained results, it was revealed that the reason for qualitative changes at different stations is due to the entry of human pollutants from various urban, industrial, mining, and agricultural sources as well as erosion in the river basin. Therefore, given the high precision of the analytical methods used in the evaluation of the qualitative aspects of the studied river’s water, it can be acknowledged that multivariable methods such as cluster analysis and factor analysis, can confidently determine the water quality of rivers and significant parameters affecting their quality and identify pollutants in the management of river water quality.https://arww.razi.ac.ir/article_3437_a6155a3a07a6e0a5cbae2ac37276d7d0.pdfwater qualityqualitative classificationmultivariate analysiscluster analysisprincipal component analysis |
| spellingShingle | Mohammad Mostafa Shabarang Ebrahim Fataei Ali Akbar Imani Hooman Bahmanpour Mohammed Shabani Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran) Journal of Applied Research in Water and Wastewater water quality qualitative classification multivariate analysis cluster analysis principal component analysis |
| title | Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran) |
| title_full | Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran) |
| title_fullStr | Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran) |
| title_full_unstemmed | Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran) |
| title_short | Evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis (Case study: the Aras river within the boundaries of Iran) |
| title_sort | evaluation of spatial qualitative changes in surface water using cluster analysis and factor analysis case study the aras river within the boundaries of iran |
| topic | water quality qualitative classification multivariate analysis cluster analysis principal component analysis |
| url | https://arww.razi.ac.ir/article_3437_a6155a3a07a6e0a5cbae2ac37276d7d0.pdf |
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