doi: 10.18178/ijesd.2016.7.8.843
Estimating the Proportional Contributions of Multiple Nitrate Sources in Shallow Groundwater with a Bayesian Isotope Mixing Model
Wen Xu1
,
Yanpeng Cai1 , ,
- 1the School of Environment, Beijing Normal University, China
- 2the Institute for Energy, Environment and Sustainable Communities, University of Regina, Canada
Abstract
In this study, a dual stable isotope approach and a Bayesian isotope mixing model (SIAR model) were applied to estimate the proportional contributions of multiple NO<sub>3</sub> <sup>-</sup> sources to shallow groundwater. The concentration of groundwater NO<sub>3</sub> <sup>-</sup> ranged widely from 5.7 to 26.2 mg/L, with the δ<sup>15</sup>N values changed from 7.1 to 11.3‰ and the δ<sup>18</sup>O values varied from 5.4 to 11.6‰. According to the classical dual isotope bi-plot, manure and sewage (M&S), soil N (Soil), NO<sub>3</sub> <sup>-</sup> in chemical fertilizer (NF), NH4 + in chemical fertilizer and precipitation (NP) were identified as the four potential NO3 - sources to groundwater. And the outputs of SIAR model showed some variability in the contribution of each NO<sub>3</sub> <sup>-</sup> source. "Soil" contributed the most (between 21% and 70%), followed by "NF" (between15% and 45%), "M&S" (between 4% and 39%), "NP" (between 0% and 20%). The SIAR model showed be considered as a reliable approach to quantify the proportional contributions of multiple NO<sub>3</sub> <sup>-</sup> sources in the mixture.
Keywords
- Dual stable isotopes
- shallow groundwater
- proportional contributions of NO3 - sources
- SIAR model
How to Cite
Wen Xu, Yanpeng Cai, Qian Tan, and Yan Xu, "Estimating the Proportional Contributions of Multiple Nitrate Sources in Shallow Groundwater with a Bayesian Isotope Mixing Model," International Journal of Environmental Science and Development, vol. 7, no. 8, pp. 581-585, 2016. https://doi.org/10.18178/ijesd.2016.7.8.843
Copyright & License
Copyright © 2016 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).