Shahid Beheshti University Advanced Environmental Sciences 3115-7173 8 2 2010 12 22 Surface Water Quality Assessment Using Cluster Analysis: a Case Study of the Gharasou River Basin, Iran Surface Water Quality Assessment Using Cluster Analysis: a Case Study of the Gharasou River Basin, Iran 95359 FA Ebrahim Fataei, epartment of Environmental Management, Graduate School of the Environment and Energy, Islamic Azad University, Science and Research Branch, Tehran, Iran. Seied Masoud Monavari Department of Environmental Management, Graduate School of the Environment and Energy, Islamic Azad University, Science and Research Branch, Tehran, Iran. Amir Hesam Hasani Department of Environmental Management, Graduate School of the Environment and Energy, Islamic Azad University, Science and Research Branch, Tehran, Iran. Seied Ahmad Mirbagheri Department of Civil Engineering, Faculty of Engineering, Kh.N.Toosi University of Technology, Tehran, Iran. Abdoreza Karbasi Department of Environmental Management and Planning, Graduate Faculty of the Environment, Tehran University, Iran Journal Article 2015 05 17 For assessment of water quality in Gharasou River, located in the Northwest of Iran, multivariate statistical analysis was used. During the period of one year, 18 physical, chemical and microbiological parameters were sampled in 11 sampling stations. The measured data were analyzed by a multivariate statistical approach, Cluster Analysis (CA). Based on CA analysis the stations were divided to three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations. The results of the study revealed that multivariate statistical techniques are an effective statistical method for water quality assessment, identification of pollution sources/factors in water quality for effective water quality management. As Extracted clustered information can be used in reducing the number of sampling sites on the River without missing much information. For assessment of water quality in Gharasou River, located in the Northwest of Iran, multivariate statistical analysis was used. During the period of one year, 18 physical, chemical and microbiological parameters were sampled in 11 sampling stations. The measured data were analyzed by a multivariate statistical approach, Cluster Analysis (CA). Based on CA analysis the stations were divided to three groups of highly polluted (HP), moderately polluted (MP), and less polluted (LP) stations. The results of the study revealed that multivariate statistical techniques are an effective statistical method for water quality assessment, identification of pollution sources/factors in water quality for effective water quality management. As Extracted clustered information can be used in reducing the number of sampling sites on the River without missing much information.

https://envs.sbu.ac.ir/article_95359_14981488235df29c0db87fb7aa15f65b.pdf