High-quality reconstruction of China's natural streamflow

Sci Bull (Beijing). 2022 Mar 15;67(5):547-556. doi: 10.1016/j.scib.2021.09.022. Epub 2021 Nov 25.


Reconstruction of natural streamflow is fundamental to the sustainable management of water resources. In China, previous reconstructions from sparse and poor-quality gauge measurements have led to large biases in simulation of the interannual and seasonal variability of natural flows. Here we use a well-trained and tested land surface model coupled to a routing model with flow direction correction to reconstruct the first high-quality gauge-based natural streamflow dataset for China, covering all its 330 catchments during the period from 1961 to 2018. A stronger positive linear relationship holds between upstream routing cells and drainage areas, after flow direction correction to 330 catchments. We also introduce a parameter-uncertainty analysis framework including sensitivity analysis, optimization, and regionalization, which further minimizes biases between modeled and inferred natural streamflow from natural or near-natural gauges. The resulting behavior of the natural hydrological system is represented properly by the model which achieves high skill metric values of the monthly streamflow, with about 83% of the 330 catchments having Nash-Sutcliffe efficiency coefficient (NSE) > 0.7, and about 56% of the 330 catchments having Kling-Gupta efficiency coefficient (KGE) > 0.7. The proposed construction scheme has important implications for similar simulation studies in other regions, and the developed low bias long-term national datasets by statistical postprocessing should be useful in supporting river management activities in China.

Keywords: Land surface model; Natural streamflow; Parameter uncertainty analysis; Reconstruction.

MeSH terms

  • China
  • Computer Simulation
  • Hydrology
  • Rivers*
  • Water Resources*