Quantitative identification, uncertainty and sensitivity analysis of nitrate sources using stable isotopes in a drinking water source watershed of Eastern China

Abstract

The quantitative identification of nitrate sources is of great significance for water resources management. Stable isotopes combined with Bayesian isotope mixing model (SIAR) model were widely used to identify nitrogen sources. However, few researchers focus on the influence of the variations of nitrate source isotopic composition on nitrate source contributions. Here, the δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻ isotopes, the SIAR model, and the uncertainty and sensitivity analysis were used to quantify the contributions and uncertainties of nitrate sources in Huashan watershed. 60 surface water samples and 82 groundwater samples were collected from November 2021 to October 2022, and atmospheric deposition (AD), chemical nitrogen fertilizer (NF), soil nitrogen (SN), and manure and sewage (M&S) were determined as the potential nitrate sources. Source identification by SIAR indicated that in November 2021 the M&S was the main contributor of nitrate to surface water, while NF was the main contributor to groundwater. In April 2022, NF contributed the most to surface water, while groundwater mainly originated from SN and MS. The variation between winter and spring sources is due to spring fertilization and rainfall. The uncertainty analysis showed that the greatest uncertainties were in SN and NF. Sensitivity analysis showed that the changes in the nitrate isotopic composition of M&S had the greatest effect on the results for δ¹⁵N, whereas only the mean values of oxygen isotope values of AD had a greater effect on the results for δ¹⁸O. Fertilizer application and changes in soil fertility due to agricultural rotations and cropping practices are intrinsic to the high level of uncertainty in SN. The magnitude of end-member standard deviations directly affects the outcomes of sensitivity analysis. We recommend prioritizing the determination of feature values for sensitive end-members during sampling. The high contribution of SN and NF highlighting the need to optimize fertilization and irrigation strategies to enhance nitrogen utilization efficiency.