A new approach to pollution vulnerability assessment in aquifers using K-means analysis

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The most used methods to evaluate the vulnerability to contamination of aquifers are based on overlay index maps, such us DRASTIC, GOD and AVI. These methods assign weighting and rating values to hydrogeological characteristics, introducing subjectivity in the evaluation. In this research, a new methodology is proposed to eliminate some of that subjectivity. The methodology evaluates the vulnerability to contamination of a detrital aquifer using K-means cluster analysis with a new set of parameters. The set is composed of some parameters extracted from these methods, as well as other new ones that have a significant influence on the movement of contaminants. Application of the Principal Components Analysis (PCA) technique before using K-means cluster allowed the selection of the most relevant parameters. To validate the methodology, this was applied to a detrital aquifer located at central Spain (the so-called “Aluviales Jarama-Tajuña” aquifer) with a significant agricultural development. To compare the traditional methods of vulnerability assessment with the K-means cluster, nitrate concentration was used as a pollution indicator. Thus, 23 groundwater quality samples were used to correlate (Spearman´s correlation coefficient) the vulnerability values with nitrate concentration to validate the most suitable method. The results showed that GOD and AVI were not appropriate methods to evaluate the vulnerability of the aquifer, because they have negative or very low correlation with nitrate concentration (− 0.5 and 0.01, respectively). This is due to the use of very few variables that do not represent relevant features for the vulnerability assessment. Alternatively, DRASTIC and K-means cluster analysis obtained higher Spearman´s correlation coefficients (0.34 and 0.48, respectively). The relevant features selected by PCA analysis to use in the K-means low-dimensional analysis were depth of groundwater (D), net recharge (R), and land use (L). The new proposed method grouped data in three clusters that represent low vulnerability (35.9% of the study area), moderate (41.4%) and high vulnerability (22.7%). K-means increases the Spearman’s correlation by 14% with respect to the most approximate conventional method (DRASTIC). Therefore, the results obtained confirm the advantage of joint application of PCA and K-Means analysis, which represents a novel approach for the assessment of groundwater vulnerability in detrital aquifers.