Artificial regulation affects nitrate sources and transformations in cascade reservoirs by altering hydrological
Gaoyang Cui1, Xiao-Dong Li2, Mengke Zhang1
1College of Geographical Science, Faculty of Geographical Science and Engineering, Henan University, Zhengzhou, 450046, China; Henan Dabieshan National Field Observation and Research Station of Forest Ecosystem, China.
Abstract:
Reservoirs are recognized as pivotal zones within the nitrate cycle, substantially modifying the source-sink dynamics of nitrate in fluvial systems. However, the impact of hydrological alterations induced by artificial regulation on nitrate sources and transformation processes in cascade hydropower reservoirs remains insufficiently comprehended. Consequently, we investigated the spatiotemporal characteristics of nitrate concentrations, δ15NNO3, δ18ONO3, δD, Δ17OH2O, relative water column stability (RWCS), runoff, and associated environmental factors within cascade reservoirs along the Wujiang River in Southwest China. The Bayesian stable isotope mixing model (MixSIAR) identified manure and sewage (M&S) as the predominant source of untreated nitrate (43.5 %) in the cascade reservoirs, with soil organic nitrogen (SON, 27.2 %), chemical fertilizer (CF, 18.5 %), and atmospheric precipitation (AP, 10.8 %) following in significance. However, evidence derived from δ15NNO3 and Δ17O isotopic values indicates that the contribution of nitrate produced by nitrification within the water body has been overlooked, accounting for 59 % in January, 40 % in July, and 24 % in October. Furthermore, the coupling of nitrification and assimilation emerged as the predominant process for nitrate transformation within the cascade reservoirs. This process was primarily regulated by RWCS and runoff (p < 0.01), indicating a substantial hydrological influence on the nitrogen cycle. This research quantifies the contribution of nitrate originating from the nitrification process within cascade reservoirs, while also addressing the limitations inherent in the traditional MixSIAR model. Additionally, it advances our comprehension of the impacts of hydrological conditions and thermal stratification on the nitrate cycle in reservoirs worldwide.
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