Determining nitrate and sulfate pollution sources and transformations in a coastal aquifer impacted by seawater intrusion-A multi-isotopic approach combined with self-organizing maps and a Bayesian mixing model

Abstract

Over the past few decades, the La Paz aquifer system in Baja California Sur, Mexico, has been under severe pressure due to overexploitation for urban water supply and agriculture; this has caused seawater intrusion and deterioration in groundwater quality. Previous studies on the La Paz aquifer have focused mainly on seawater intrusion, resulting in limited information on nitrate and sulfate pollution. Therefore, pollution sources have not yet been identified sufficiently. In this study, an approach combining hydrochemical tools, multi-isotopes (δ²H_H2O, δ¹⁸O_H2O, δ¹⁵N_NO3, δ¹⁸O_NO3, δ³⁴S_SO4, δ¹⁸O_SO4), and a Bayesian isotope mixing model was used to estimate the contribution of different nitrate and sulfate sources to groundwater. Results from the MixSIAR model revealed that seawater intrusion and soil-derived sulfates were the predominant sources of groundwater sulfate, with contributions of ~43.0% (UI₉₀ = 0.29) and ~42.0% (UI₉₀ = 0.38), respectively. Similarly, soil organic nitrogen (~81.5%, UI₉₀ = 0.41) and urban sewage (~12.1%, UI₉₀ = 0.25) were the primary contributors of nitrate pollution in groundwater. The dominant biogeochemical transformation for NO₃^- was nitrification. Denitrification and sulfate reduction were discarded due to the aerobic conditions in the study area. These results indicate that dual-isotope sulfate analysis combined with MixSIAR models is a powerful tool for estimating the contributions of sulfate sources (including seawater-derived sulfate) in the groundwater of coastal aquifer systems affected by seawater intrusion.

Keywords: Bayesian isotope mixing model; Coastal aquifer; Nitrate isotopes; Self-organizing maps; Sulfate isotopes; Uncertainty analysis.