Tracking the sources and fate of nitrate pollution by combining hydrochemical and isotopic data with a statistical approach

This study contributes to identifying and spatializing the different types of nitrate sources by combining hydrogeochemical and isotopic data with principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) multicriteria statistical methods. The methodology is applied to the strategic Mons Basin chalk aquifer (Belgium). The results are based on a whole dataset containing 72 water samples with analyses of the hydrogeochemical parameters (temperature, pH, electrical conductivity (EC), redox potential, dissolved O2), alkalinity, total organic carbon (TOC), silica (SiO2), major and minor ions (NO3-, NH4+, Ca2+, dissolved Fe and Mn, K+, Mg2+, Na+, Sr2+, Cl-, F-, SO4-, B) and multiple stable isotope ratios (δ11B, δ15N–NO3-, δ18O–NO3-). Compared to classical PCA, the recently developed t-SNE method, which considers non-linear relationships between variables and preserves local-scale similarities in a low-dimensional space, showed much better performance in discriminating different groups of samples and related zones in the aquifer. t-SNE results combined with isotope ratios highlighted four zones in the aquifer (grouped as A to D) and the presence of denitrification fronts. Group A presents a manure signature (δ15N-NO3- – mean (µ) +12.78‰, standard deviation (σ) 6.48‰; δ11B – µ 29.96‰, σ 6.91‰). Group B exhibits both manure and inorganic fertilizer signatures (δ15N-NO3- – µ 6.27‰, σ 2.55‰; δ11B – µ 15.86‰, σ 9.69‰). Group C shows a contamination by sewage (δ15N-NO3- – µ 12.67‰, σ 5.60‰; δ11B – µ 9.97‰, σ 7.08‰). Group D presents a mixed signature (δ15N-NO3- – µ 9.25‰, σ 2.94‰; δ11B – µ 20.00‰, σ 6.70‰).