Multivariate Characterization of Hydrochemically Similar Groundwaters: Resolving Hydrochemical Structure and Process-Related Variability

Groundwater systems sharing similar major-ion facies may still differ in their hydrochemical organization and mineralization pathways, particularly in structurally complex aquifer settings. This study evaluated multivariate chemometric approaches for investigating two hydrochemically similar groundwater systems (MAJA and MAJA2) examined within the regulatory framework for natural mineral water recognition. The dataset consisted of a 13-month monitoring campaign complemented by an independent multi-year validation dataset. Hydrochemical variables were organized into chemical and process-related blocks, including major ions, physicochemical parameters, D’Amore indices, and mineral saturation indices. SIMCA was applied to evaluate the intra-class hydrochemical structure, and OPLS-DA was used to investigate predictive and orthogonal sources of variability. Model robustness and parameter reproducibility were assessed using jackknife resampling, Leave-One-Month-Out cross-validation, repeated double cross-validation, and permutation testing. SIMCA identified PC1 as the only consistently reproducible latent component across resampling iterations. An exploratory Structural Response Coefficient (Rj) was introduced as a model-derived descriptor integrating explained and residual variance within the SIMCA model. OPLS-DA models showed stable class-related latent structures under nested validation conditions. Electrical conductivity, sulphate, potassium, SI_gypsum, SI_halite, and D’Amore index A were the variables most consistently associated with discriminant variability. Stable isotope data indicated a common meteoric origin and similar recharge conditions for both systems. The results illustrate how multivariate chemometric analysis, combined with stability-oriented validation procedures, may aid the interpretation of hydrochemical variability in compositionally similar groundwater systems.