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<p>Limited streamflow observations have constrained long-term hydrological assessment and water resources management in the Amur River Basin, the largest transboundary river in Northeast Asia. To overcome this limitation, we reconstructed two monthly streamflow datasets—representing naturalized and human-influenced conditions—at 6 arcmin (~0.1°) spatial resolution for the period 1902–2022 using the Common Land Model coupled with the CaMa-Flood river routing model. Human-influenced streamflow considers major anthropogenic processes, including land use and land cover change, water withdrawals, and reservoir regulation. Evaluation against data from five major gauge stations shows satisfactory performance, with Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) generally exceeding 0.50. These datasets not only capture the long-term hydroclimatic variability across the basin, but also reveal the cumulative influence of anthropogenic processes on streamflow magnitude and seasonality. These century-scale, internally consistent datasets provide new opportunities for characterizing the spatial and temporal variability of streamflow, advancing streamflow variability attribution, supporting basin-wide water resources planning, and promoting sustainable management in Northeast Asia.</p>

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Naturalized and human-influenced streamflow of the Amur River for century-scale hydrological assessment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月3日

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  • Yunfei Feng,
  • Yu Li,
  • Bingyao Zhang,
  • Shupeng Zhang,
  • Tongtiegang Zhao,
  • Chi Zhang

摘要

Limited streamflow observations have constrained long-term hydrological assessment and water resources management in the Amur River Basin, the largest transboundary river in Northeast Asia. To overcome this limitation, we reconstructed two monthly streamflow datasets—representing naturalized and human-influenced conditions—at 6 arcmin (~0.1°) spatial resolution for the period 1902–2022 using the Common Land Model coupled with the CaMa-Flood river routing model. Human-influenced streamflow considers major anthropogenic processes, including land use and land cover change, water withdrawals, and reservoir regulation. Evaluation against data from five major gauge stations shows satisfactory performance, with Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) generally exceeding 0.50. These datasets not only capture the long-term hydroclimatic variability across the basin, but also reveal the cumulative influence of anthropogenic processes on streamflow magnitude and seasonality. These century-scale, internally consistent datasets provide new opportunities for characterizing the spatial and temporal variability of streamflow, advancing streamflow variability attribution, supporting basin-wide water resources planning, and promoting sustainable management in Northeast Asia.