Groundwaters, like other natural waters, are solutions of a variety of substances in the solvent water. Man's impact upon groundwater systems has created many environmental problems so that hydrochemical studies related to pollution have become very important. In this context high abundance of nitrogen species, particularly nitrate, can cause adverse health effects, their main sources being fertilizer, animal or human waste, natural soil organic matter, nitrogen fixation and rain. Graphical representations of hydrochemical data (for example molar ratio diagrams, stochiometric diagrams, triangular diagrams, mixing diagrams) pose considerable problems if statistical evaluations have to be performed. In fact, since hydrochemical data are compositional (proportional data), their sample space is the simplex, a constrained space where the application of the Euclidean geometric principles gives us misleading information. In this paper classical binary diagrams have been substituted by new equivalent graphs coherent with the properties of compositional data, thus opening new perspectives in the evaluation of geochemical processes affecting water chemistry. Moreover, since nitrogen species in the database are often affected by the presence of numerous data below the detection limit, the role of their presence was investigated. Several approaches coherent with compositional data analysis theory were applied and interesting indications were obtained about 1) the loss of information and 2) the effect on the variance- covariance structure of the whole composition (anions, cations) when nitrogen data below the detection limit are a priori eliminated.