HJ-Biplot and Clustering Techniques for Analyzing Water Quality: A Case Study

Water quality is a critical concern for humanity, given the profound impact of polluted or contaminated water on human health. Statistical analysis tools play a pivotal role in the assessment of water quality, and recent studies have examined the individual biological, chemical, and physical variables involved. Still, it is important to extract relevant information that comes from the interaction between these variables. In this research, we take, as a case study, the Guano river in Ecuador, and use a two-way multivariate analysis HJ-Biplot, and clustering techniques with data collected from this river, containing information about 14 variables. Three analyses were conducted from different points of view. The results were conclusive in determining that the river exhibits high levels of contamination, especially in the most densely populated and tourist areas. They also support the importance of analyzing water quality systems as complex entities, emphasizing the interaction between variables.