Robust multivariate statistics for decision-making in water resource management: Classical PCA versus MacroPCA in Ecuador
DOI:
https://doi.org/10.70577/cieninter.v4i3.88Keywords:
Decision making, robust multivariant stadistics, statistical analysis, water resources managementAbstract
This study analyzes the relationship between ecological and physical-chemical conditions in eleven Ecuadorian hydrographic basins in 1995 and 2021 using robust and multivariate methods, such as Detect Deviating Cells (DDC), Principal Component Analysis (PCA), MacroPCA and HJ-BIPLOT on the data collected by the Undersecretariat of the Ministry of the Environment, Water and Ecological Transition of Ecuador. For which, outliers were identified, highlighting high levels of contamination in certain samples from 1995. However, according to the comparative analysis between traditional PCA and MacroPCA, it suggests that the latter better adjusts the variance, better explaining the year 2021 which was influenced due to the context of the pandemic. In the same way, a significant correlation is found only between the ecological variables and the physical-chemical richness variable. In turn, through the HJ-biplot the groupings of the two observed years are visualized, highlighting the complex relationship between environmental conditions and the evolution of species in the Ecuadorian hydrographic basins, given that it is evident that the year 1995 offers better conditions for the preservation of species than the year 2021. These findings underscore the importance of continuing to monitor these vital ecosystems.
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Copyright (c) 2026 MSc. Ricardo Rubén Mora Torosine, Mg. Mauricio Rubén Franco Coello, MSc. Luz María Quinde Arreaga, MSc. Verónica Alexandra Arrata Corzo
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