Quantification of nitrate sources and fates in rivers in an irrigated agricultural area using environmental isotopes and a Bayesian isotope mixing model

Abstract

Nitrate (NO₃^-) pollution in rivers caused by intensive human activities is becoming a serious problem in irrigated agricultural areas. To identify NO₃^- sources and reveal the impact of irrigation projects on NO₃^- pollution in rivers, the hydrochemistry and isotopes of irrigation water from the Yellow River (IW) and river water (RW), and potential source samples were analyzed. The mean NO₃^- concentrations in the IW and RW were 24.4 mg/L and 49.9 mg/L, respectively. Approximately 45.2% of RW samples (n = 31) exceeded the Chinese drinking water standard for NO₃^- (45 mg/L). The δ¹⁵N and δ¹⁸O values, combined with the Cl^-/Na⁺, SO₄^2-/Ca²⁺ ratio distributions, indicate that the NO₃^- in the RW mainly originated from chemical fertilizers, manure and sewage. A Bayesian model showed that manure and sewage contributed the most to the overall NO₃^- levels of the IW. In the RW, chemical fertilizers and IW contributed the most to the overall NO₃^- levels. The mean nitrate contribution to the RW from the combination of chemical fertilizers and IW is estimated to be 51.6%. Nitrogen from manure and sewage, soil N and precipitation also contributed. The NO₃^- pollution in rivers was largely influenced by the irrigation regime, with a large amount of nitrogen in chemical fertilizer lost because of low utilization efficiency and subsequent transfer, via irrigation runoff, into the rivers. This study suggests that with a detailed assessment of the sources and fate of NO₃^-, effective reduction strategies and better management practices can be implemented to control NO₃^- pollution in rivers.

Keywords: Bayesian model; Irrigated agricultural region; Irrigation water; Isotope; Nitrate pollution; River.