Spatio-Temporal Variations in Nitrate Sources and Transformations in the Midstream of the Yellow River Determined Based on Nitrate Isotopes and Hydrochemical Compositions

Nitrate pollution is a major environmental problem threatening rivers, and nitrogen and oxygen isotopes have proved to be an effective means of analyzing the sources and transformations of nitrate in rivers. However, a low monitoring frequency cannot accurately reflect the changes in nitrate. In this study, the sources and transformations of nitrate in the middle reaches of the Yellow River and its tributaries during the dry season and the wet season were analyzed based on water quality parameters and nitrate isotopes. Stable isotope analysis conducted using the R (SIAR) model was used to estimate the proportions of different nitrate sources. The results showed that the main nitrate sources in the main stream were soil nitrogen (40.95&ndash:45.83%) and domestic sewage and manure (30.93&ndash:32.60%), respectively, with little variation between the dry season and wet season because of the large flow of the Yellow River. During the dry season, the nitrate sources of the two tributaries were mainly domestic sewage and manure (45.23&ndash:47.40%), followed by soil nitrogen (31.35&ndash:34.00%). However, the primary nitrate source of T2 (Qin River) became soil nitrogen (40.05%) during the wet season, a phenomenon that was mainly caused by the significant increase in river discharge and in soil erosion in the basin. During the wet season, the concentrations of total nitrogen (TN) and nitrate (NO3&minus:) significantly decreased in the main stream and tributaries, and nitrification and denitrification processes occurred in both the main stream and tributaries of the Yellow River. In addition, the T2 tributary (Qin River) was also significantly affected by mixed dilution. High-frequency sampling can reflect the isotopic information of nitrate in the river more comprehensively, which helps us to understand the conversion process of nitrate more accurately.