Nitrate behaviors and source apportionment in an aquatic system from a watershed with intensive agricultural activities

Abstract

Nitrate pollution in aquatic systems caused by intensive agricultural activities is a serious problem in the Sanjiang Plain. In this study, a dual isotope approach (δ¹⁵N–NO₃⁻ and δ¹⁸O–NO₃⁻) was employed to identify potential nitrate sources (atmospheric deposition, AD; NO₃⁻ derived from soil organic matter nitrification, NS; NO₃⁻ derived from chemical fertilizer nitrification, NF; and manure and sewage, M&S) and transformation processes occurring in the Abujiao River watershed located in the Sanjiang Plain. The Bayesian model (stable isotope analysis in R, SIAR) was utilized to apportion the contribution of the potential sources. In this watershed, the nitrate concentrations in the surface water were low (mean ± SD = 1.15 ± 0.84 mg L⁻¹), and were greatly influenced by precipitation and land use conditions during the two sampling periods (the high flow period, September; the low flow period, November). On the contrary, in the ground water, high NO₃⁻ concentrations were observed (7.84 ± 5.83 mg L⁻¹) and no significant temporal variation in NO₃⁻ was found during the sampling periods. The sampled water δ¹⁸O–NO₃⁻ values suggest that the nitrification process was not the main N cycling process, because most of the measured δ¹⁸O–NO₃⁻ values were above the expected δ¹⁸O–NO₃⁻ from nitrification throughout the sampling periods. Both the chemical and isotopic characteristics indicated that the signs of de-nitrification were absent in the surface water. However, significant de-nitrification processes were observed in the ground water for all sample periods. Results from the SIAR model showed that source contributions differed significantly during the two sampling periods. During the high flow period, chemical fertilizers and soil N fertilizer equally contributed to the major sources of nitrate in the surface water. In contrast, manure and sewage sources dominated the source contribution during the low flow period (November). This study suggested that with the assessment of the behaviors and sources of NO₃⁻, effective nitrate reduction strategies and better management practices can be implemented to protect water quality.