Assessment of social vulnerability to groundwater pollution using K-means cluster analysis

It is possible to assess the harm that society suffers as a consequence of groundwater contamination in aquifers. Indexing methodologies are commonly applied to assess the social vulnerability to polluted aquifers. However, they assign weighting and rating values to the different factors involved, which makes them very subjective. This research aims to assess the social vulnerability to groundwater pollution taking into account three factors: the uses of groundwater resources, the exposed population, and the socio-economic losses. In order to eliminate the subjectivity of current indexing methodologies, this work uses a K-means cluster analysis for the assessment of social vulnerability. With this method, a social vulnerability map can be produced with greater objectivity. The proposed methodology is applied to an aquifer located in central Spain, an area with significant agricultural development. Low population density and unproductive zones result in low social vulnerability in most of the area. However, high social vulnerability is observed in the southern sector due to agricultural development, which leads to higher socio-economic variables and demand for groundwater resources. Similarly, high social vulnerability is observed in the northeast, mainly influenced by the groundwater use and the exposed population. These results show that social vulnerability in most of the study area is not very significant for assessing the risk of groundwater contamination, because the damage to the social, environmental, or economic sector is low. However, in the south and northeast of the study area, pesticides and fertilizers should be used with caution, as they significantly increase the risk of groundwater contamination. The K-means clustering method proved to be an objective and reliable option for assessing social vulnerability to groundwater pollution in aquifers.