Abstract
The quantitative identification
of nitrate sources is of great significance for the control of non-point
source pollution and the comprehensive management of water resources in
watersheds.
δ15N-NO3- and
δ18O-NO3- isotopes
combined with the Bayesian isotope
mixing model were widely used as effective methods to identify nitrogen
sources. In this study, a total of 60
surface water samples and 82 groundwater samples were collected in study
area 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 (mean 38.1%),
while NF was the main contributor to groundwater (mean 39.8%). In April
2022, NF contributed the most to surface water (38.3%), while
groundwater mainly originated from SN (29.4%) and MS (29.8%). The
uncertainty analysis showed that the greatest uncertainties were in SN
and NF, followed by M&S and AD. 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. The sensitivity analysis results can
optimize the sampling scheme and improve the accuracy of the model
predictions. Additionally, the contributions of soil nitrogen and
nitrogen fertilizer to nitrate in surface water and groundwater reached
58% and 64%, respectively. Therefore, optimizing fertilizer and
irrigation management is necessary to improve nitrogen use efficiency in
watershed management.
Keywords: Nitrate, Isotope, Bayesian isotope mixing model,
Uncertainty analysis, Sensitivity analysis.