Deciphering the impact of cascade reservoirs on nitrogen transport and nitrate transformation: Insights from multiple isotope analysis and machine learning.

Journal: Water research
PMID: 39432994

Abstract

Construction of cascade reservoirs has altered nutrient dynamics and biogeochemical cycles, thereby influencing the composition and productivity of river ecosystems. The Lancang River (LCR), characterized by its cascade reservoir system, presents uncertainties in nitrogen transport and nitrate transformation mechanisms. Herein, we conducted monthly monitoring of hydrochemistry and multiple stable isotopes (δN-NO, δO-NO, δO-HO, δD-HO) throughout 2019 in both the natural river reach (NRR) and cascade reservoirs reach (CRR) of the LCR. Through the monthly detection of nitrogen forms and runoff in the import (M2) and export (M9) section, the average annual retention ratios for Total nitrogen (TN), Nitrate nitrogen (NO-N), Particulate Nitrogen (PN) and Ammonium Nitrogen (NH-N) were about -35%, -53%, 48% and -65%, respectively. The retention rates were positively correlated with hydraulic retention time and negatively correlated with reservoir age, especially in the flood season. Compared to the NRR, the reservoir had significantly affected the nitrogen transport characteristics, especially for the large reservoirs (like Xiaowan and Nuozhadu), which enhanced phytoplankton uptake of NO-N to form PN capabilities in the lentic environment and subsequently to precipitate or intercept it at the reservoir. This led to the overall decreasing trend of TN and PN concentrations along the CRR. The Bayesian stable isotope model quantified NO-N sources from the NRR to the CRR. During this transition, soil nitrogen (SN) ratios decreased from 69.3% to 61.8%, while Manure & sewage (M&S) increased from 24.0% to 31.3%. Anthropogenic and natural factors, including urban sewage discharge, population density, and precipitation, were selected as key predictor variables. The eXtreme Gradient Boosting (XGBoost) model exhibited superior predictive performance for NO-N concentrations, achieving an R of 0.70. These findings deepen our understanding of the impact of reservoirs on river ecology.

Authors

  • Yufei Bao
    State Key Laboratory of Watershed Water Cycle Simulation and Regulation, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.
  • Yuchun Wang
    School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China; School of Arts and Science, Suqian University, Suqian, 223800, China. Electronic address: wychun113@163.com.
  • Mingming Hu
    State Key Laboratory of Watershed Water Cycle Simulation and Regulation, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.
  • Peng Hu
    The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Nanping Wu
    Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; School of Civil Engineering & Architecture, Wuhan University of Technology, Wuhan 430070, China.
  • Xiaodong Qu
    State Key Laboratory of Watershed Water Cycle Simulation and Regulation, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.
  • Xiaobo Liu
    Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang 110169, China.
  • Wei Huang
    Shaanxi Institute of Flexible Electronics, Northwestern Polytechnical University, 710072 Xi'an, China.
  • Jie Wen
    Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, 518055, Guangdong, China; Shenzhen Medical Biometrics Perception and Analysis Engineering Laboratory, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, Guangdong, China.
  • Shanze Li
    State Key Laboratory of Watershed Water Cycle Simulation and Regulation, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; Department of Water Ecology and Environment, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.
  • Meng Sun
    Department of Gynecology, The Second People's Hospital of Shenzhen, Shenzhen, China.
  • Qian Zhang
    The Neonatal Intensive Care Unit, Peking Union Medical College Hospital, Peking, China.

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