This study aimed to determine the reliability of the double-clustering method to understand the spatial association and distribution of major and minor constituents in the groundwater of an arid endorheic basin in central Mexico (Comarca Lagunera Region). The results of the double-clustering approach were compared with well-known spatial statistics such as spatial autocorrelations (Moran index) and the local indicator of spatial association (LISA). Fifty-five groundwater samples were collected from diverse wells within the basin, and the major ions, metalloids, and trace elements were determined. Overall, the double-clustering analysis was an effective tool for identifying lithogenic/anthropogenic processes occurring in the basin and for establishing zones with high or low abundance of major ions and trace elements, even where processes affecting the groundwater quality were spatially dispersed. Although 89% of the samples showed As higher than the threshold value of 10 μg/L proposed by the World Health Organization for drinking water, both the double-clustering and LISA analyses identified As hotspots in the alluvial aquifer, where the extraction of deeper and warmer groundwater might promote the concomitant release of the metalloids As, Sb, and Ge and the trace elements V and W. Similarly, both statistical analyses identified mountainous sectors where the weathering of silicates and carbonates plays a key role in the abundance of HCO3-, Ga, and Ba. However, the LISA analysis failed to identify hotspots of carbonate-derived elements such as Ca, Mg, Sr, and U and silicate-derived elements such as Ca, Mg, K, Sr, Rb, Cs, Pb, Ni, and Y. Otherwise, the double-clustering analysis clearly defined high- and low-concentration zones for all these elements in the study region. Unlike the LISA analysis, the double-clustering approach was also successful in determining alluvial areas with high concentrations of Si and Ti and areas where the concentrations of Na, Cl-, SO42-, NO3-, B, Li, Cu, Re, and Se in groundwater were elevated, increasing the groundwater salinity. Overall, this study demonstrated that the double-clustering is an easy-to-apply approach, capable of visualizing disperse zones where specific anthropogenic processes may threaten the groundwater quality