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Combining multi-isotope technology, hydrochemical information, and MixSIAR model to identify and quantify nitrate sources of groundwater and surface water in a multi-land use region

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Abstract

Accurate identification of nitrate (NO3−) sources is the premise of non-point source pollution control in watersheds. The multiple isotope techniques (δ15N-NO3−, δ18O-NO3−, δ2H-H2O, δ18O-H2O), combined with hydrochemistry characteristics, land use information, and Bayesian stable isotope mixing model (MixSIAR), were used to identify the sources and contributions of NO3− in the agricultural watershed of the upper Zihe River, China. A total of 43 groundwater (GW) and 7 surface water (SFW) samples were collected. The results showed that NO3− concentrations of 30.23% GW samples exceeded the WHO maximum permissible limit level, whereas SFW samples did not exceed the standard. The NO3− content of GW varied significantly among different land uses. The averaged GW NO3− content in livestock farms (LF) was the highest, followed by vegetable plots (VP), kiwifruit orchards (KF), croplands (CL), and woodlands (WL). Nitrification was the main transformation process of nitrogen, while denitrification was not significant. Hydrochemical analysis results combined with NO isotopes biplot showed that manure and sewage (M&S), NH4+ fertilizers (NHF), and soil organic nitrogen (SON) were the mixed sources of NO3−. The MixSIAR model summarized that M&S was the main NO3− contributor for the entire watershed, SFW, and GW. For contribution rates of sources in GW of different land use patterns, the main contributor in KF was M&S (contributing 59.00% on average), while M&S (46.70%) and SON (33.50%) contributed significantly to NO3− in CL. Combined with the traceability results and the situation that land use patterns are changing from CL to KF in this area, improving fertilization patterns and increasing manure use efficiency are necessary to reduce NO3− input. These research results will serve as a theoretical foundation for controlling NO3− pollution in the watershed and adjusting agricultural planting structures.

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Funding

This work was supported by the Groundwater Nitrate Traceability Project in Boshan District (Grant number 1460021014); the National Natural Science Foundation of China (Grant number 41977144); and the Agricultural Major Technology Collaborative Promotion Plan of Shandong province (Grant number SDNYXTTG-2022–22).

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Authors and Affiliations

  1. Environment Research Institute, Shandong University, Binhai Road 72, Qingdao, 266237, China

    Wanning Zhao, Liyong Bai, Shuangshuang Li, Dongmei Liu & Jiulan Dai

  2. Water Conservancy Bureau of Boshan District, Zibo, 255200, China

    Deqing Yang

  3. Water Conservancy Bureau of Zibo Municipality, Zibo, 255022, China

    Qiang Sun

  4. School of Life Sciences, Qufu Normal University, Qufu, 273165, China

    Yandong Gan

Authors
  1. Wanning Zhao
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  2. Deqing Yang
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  3. Qiang Sun
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  6. Shuangshuang Li
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Contributions

Wanning Zhao: Conceptualization, Methodology, Software, Formal analysis, Investigation, Writing-original draft, Writing-review and editing.

Deqing Yang: Conceptualization, Methodology, Writing-review and editing.

Qiang Sun: Methodology, Writing-review and editing.

Yandong Gan: Methodology, Writing-review and editing.

Liyong Bai: Methodology, Investigation, Writing-review and editing.

Shuangshuang Li: Methodology, Investigation.

Dongmei Liu: Methodology, Investigation.

Jiulan Dai: Conceptualization, Methodology, Formal analysis, Investigation, Writing-original draft, Writing-review and editing.

Corresponding author

Correspondence to Jiulan Dai.

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Highlights

• Soil organic nitrogen, manure, and sewage are the main sources of nitrate in the upstream area of Zihe River.

• Hydrochemical information combined with multi-isotope technology and Bayesian isotope mixing model is a practical method for joint traceability.

• The results will provide basic data for regional water resource protection and a reference for effective water resource management in multi-land use areas.

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Zhao, W., Yang, D., Sun, Q. et al. Combining multi-isotope technology, hydrochemical information, and MixSIAR model to identify and quantify nitrate sources of groundwater and surface water in a multi-land use region. Environ Sci Pollut Res 30, 80070–80084 (2023). https://doi.org/10.1007/s11356-023-27720-9

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