Evidence map›Paper›PMID 40522969›Full record

ArticlePloS one2025

Vertical distribution characteristics and source apportionment of nitrogen in the Longyangxia Reservoir in the upper reaches of the Yellow River.

Wei Wu, Yuhe Dong, Chen Li, Hang Chen, Lei Ren, Sheng Xu

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Wei WuState Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, Shaanxi, China.ORCID 0000-0002-6625-2222
Yuhe DongState Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, Shaanxi, China.
Chen LiState Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, Shaanxi, China.
Hang ChenState Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, Shaanxi, China.
Lei RenState Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, Shaanxi, China.
Sheng XuState Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi'an University of Technology, Xi'an, Shaanxi, China.

Funding

National Natural Science Foundation of China U2243242
6 · The paper itself

Abstract

Studying the biogeochemical cycle of biogenic nitrogen and its influence on hydrological processes and anthropogenic nitrogen input is of great significance for water resource management and the maintenance of aquatic ecosystems in ecologically sensitive areas. Currently, there is a limited understanding of the sources contributing to nitrate levels during thermal stratification in deep and large reservoirs, as well as the transformation processes of nitrate under varying hydrological conditions. This study collected water samples from the Longyangxia Reservoir, located in the upper reaches of the Yellow River, during January and April of 2024. Utilizing hydrogeochemical analysis, multivariate stable isotope technology, the Bayesian isotope mixing model, and multivariate statistical analysis, we analyzed the vertical distribution characteristics of nitrogen in the reservoir across different periods. The transformations and sources of nitrogen were identified, and the contribution rates of each nitrogen source were estimated. The results indicate that January serves as the mixing period for the Longyangxia Reservoir, during which the differences in nitrogen concentration among the vertical water layers are relatively minimal. The concentration ranges for nitrate (NO₃⁻), dissolved organic nitrogen (DON), and ammonium (NH₄⁺) were observed to be 0.598-0.647 mg/L, 0.124-0.397 mg/L, and 0.015-0.157 mg/L, respectively. Beginning in April, the reservoir enters the thermal stratification period, characterized by higher concentrations of various nitrogen forms compared to the mixing period. During the stratification period, the concentration of various nitrogen forms within the vertical profile of the reservoir demonstrates a characteristic distribution of being low in the upper section, maximum values of total nitrogen (TN) and dissolved DON in the middle section, and maximum concentrations of NO₃⁻ and NH₄⁺ in the bottom section. Nitrate nitrogen and dissolved organic nitrogen are the primary forms of nitrogen present in the Longyangxia Reservoir, constituting 66.71% and 25.83% of the total dissolved nitrogen in January, and 62.39% and 21.59% in April, respectively. During the sampling period at Longyangxia Reservoir, the δ15N-NO3- values in the water ranged from 5.58 ‰ to 7.38 ‰, while the δ18O-NO3- values varied from -5.87 ‰ to 2.58 ‰. Nitrification is identified as the primary nitrogen conversion process occurring in the reservoir water. Under aerobic conditions, denitrification does not occur in aquatic environments. The dynamics of nitrate in the bottom layer are influenced by nitrification processes and the release of nitrogen from sediment. Soil organic nitrogen is the primary source of nitrate in Longyangxia water, contributing 42.1% and 51.8% during the sampling period, respectively. This study introduced sediment as an additional end member, highlighting that the contribution of sediment to nitrate in water is significant, accounting for 24% and 14.1%, respectively. This study offers valuable insights for precise nitrogen management and control in deep reservoirs by tracking nitrate sources and quantifying their contributions.

Indexed as

NitrogenRiversWater Pollutants, ChemicalAmmonium CompoundsBayes TheoremChinaEcosystemEnvironmental MonitoringNitratesAmmonium CompoundsNitratesNitrogenWater Pollutants, Chemical

Identifiers

PMID40522969
PMCPMC12169569

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