Determination of water quality indicator using deep hierarchical cluster analysis

• Published in: Urban climate 2023-05, Vol.49, p.101468, Article 101468
• Main Authors: Shenbagalakshmi, G., Shenbagarajan, A., Thavasi, S., Gomathy Nayagam, M., Venkatesh, R.
• Format: Article
• Language: English
• Subjects: Clustering; Contaminants; Ground water; Hydrochemical; Industrial zones; Water quality
• ISSN: 2212-0955; 2212-0955
• DOI: 10.1016/j.uclim.2023.101468

The past decade has seen notable impact of man on the environment due to first-time increase in population and rapid rate of urbanization with the strengthening and development in agricultural practices. This has lead to progressive and frequent degradation of resources especially ground water. In this paper, we study the features of ground water from the industrial zones around Chennai. The research aims to understand the factors influencing the water quality parameters and determines the water quality index (WQI). To examine whether or not the data on the water quality can be categorized into hydrochemical groups, a hierarchical cluster analysis (HCA) is utilized. The groundwater samples were divided up into significantly distinct subsets by the use of hierarchical cluster analysis. The water standards are considered as inputs to determine the groundwater vulnerability and ranks are determined based on the decision variables. The simulation is conducted form the input collected data using python simulator, and the results are tested in terms of determining the accuracy of classifying the water quality samples. The findings demonstrate that the suggested strategy finds the WQI in the industrial zones with a greater rate of accuracy. •Water quality issues are difficult and varied, plays vital concentration and action to origin toward the hydrological cycle.•The research aims to know the factors including the water quality parameters and determines the water quality index (WQI).•Water quality has been categorized into hydrochemical groups, a hierarchical cluster analysis (HCA) is utilized.•The water standards as inputs to the groundwater vulnerability and ranks are determined depending on decision variables.•The findings demonstrate that the suggested strategy finds the WQI in the industrial zones with a greater rate of accuracy.