Ecological Indicators (Dec 2024)

Long-term water quality dynamics and trend assessment reveal the effectiveness of ecological compensation: Insights from China’s first cross-provincial compensation watershed

  • Haitao Chen,
  • Chengcheng Wang,
  • Qiuru Ren,
  • Xia Liu,
  • Jiaxue Ren,
  • Gelin Kang,
  • Yuqiu Wang

Journal volume & issue
Vol. 169
p. 112853

Abstract

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Despite the global adoption of watershed Payments for Ecosystem Services (PES) to enhance water quality, their effectiveness in achieving improvements remains inadequately assessed. This study employed the Weighted Regressions on Time, Discharge, and Season (WRTDS) model to evaluate water quality changes in China’s first cross-provincial Ecological Compensation (EC) watershed from 2000 to 2020, and to determine the impact of human interventions and climate change. Results showed that the WRTDS model accurately predicted concentrations and loads of TN, NH4+, CODMn, and TP, while human interventions, including WWTPs construction and EC measures, have improved water quality to varying extents. Specifically, NH4+ concentrations rose sharply from 2000 to 2008 but decreased during the EC period, indicating effective wastewater treatment. However, TN concentrations continued to rise, and TP levels did not significantly decrease, probably due to the accumulation legacy N and P in soil and groundwater. Moreover, CODMn concentrations exhibited a steady increased from 2000 to 2020. These trends collectively suggest that point source pollution controls are effective, while non-point source pollution, particularly legacy sources, remains a considerable challenge. In addition, water quality variations under different climate conditions reveal the diversity of potential pollution sources, while extreme precipitation events potentially increasing TN, CODMn, and TP concentrations. Overall, the WRTDS model effectively evaluates the watershed EC programmes, identifies long-term water quality trends and potential sources, and offers valuable insights for optimizing pollution control strategies.

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