Identification of groundwater nitrate sources in an urban aquifer (Alborz Province, Iran) using a multi-parameter approach.

High concentrations of NŌ in water resources are detrimental to both human health and aquatic ecosystems. Identification of NŌ sources and biogeochemical processes is a crucial step in managing and controlling NŌ pollution. In this study, land use, hydrochemical data, dual stable isotopic ratios and Bayesian Stable Isotope Mixing Models (BSIMM) were integrated to identify NŌ sources and estimate their proportional contributions to the contamination of the Karaj Urban Aquifer (Iran). Elevated NŌ concentrations indicated a severe NŌ pollution, with 39 and 52% of groundwater (GW) samples displaying the concentrations of NŌ in exceedance of the World Health Organization (WHO) standard of 50 mg NŌ L in the rainy and dry seasons, respectively. Dual stable isotopes inferred that urban sewage is the main NŌ source in the Karaj Plain. The diagram of NŌ/Cl‾ versus Cl‾ confirmed that municipal sewage is the major source of NŌ. Results also showed that biogeochemical nitrogen dynamics are mainly influenced by nitrification, while denitrification is minimal. The BSIMM model suggested that NŌ originated predominantly from urban sewage (78.2%), followed by soil organic nitrogen (12.2%), and chemical fertilizer (9.5%) in the dry season. In the wet season, the relative contributions of urban sewage, soil nitrogen and chemical fertilizer were 87.5, 6.7, and 5.5%, respectively. The sensitivity analysis for the BSIMM modeling indicates that the isotopic signatures of sewage had the major impact on the overall GW NŌ source apportionment. The findings provide important insights for local authorities to support effective and sustainable GW resources management in the Karaj Urban Aquifer. It also demonstrates that employing Bayesian models combined with multi-parameters can improve the accuracy of NŌ source identification.