Literature DB >> 29886338

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

Yan Zhang1, Peng Shi2, Fadong Li3, Anlei Wei1, Jinxi Song1, Junjie Ma1.   

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+, SO42-/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.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

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

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Year:  2018        PMID: 29886338     DOI: 10.1016/j.chemosphere.2018.05.164

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  2 in total

1.  Lake water phosphate reduction with advanced wastewater treatment in watershed, at Lake Hamana, Shizuoka Prefecture, Japan, from 1995 to 2016.

Authors:  Atsushi Kubo; Rin Imaizumi; Satoru Yamauchi
Journal:  Environ Sci Pollut Res Int       Date:  2019-11-26       Impact factor: 4.223

2.  Coupling the dual isotopes of water (δ2H and δ18O) and nitrate (δ15N and δ18O): A new framework for classifying current and legacy groundwater pollution.

Authors:  Julie N Weitzman; J Renée Brooks; Paul M Mayer; William D Rugh; Jana E Compton
Journal:  Environ Res Lett       Date:  2021-03-24       Impact factor: 6.793

  2 in total

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