China's high-quality natural gauge-based streamflow dataset (CNRD_gauge) was developed from a well-trained and tested land surface model (VIC) that coupled to a routing model with flow direction correction. The dataset currently covers multiple hydrological stations for the period 1961–2018 , and will continue to update. The land surface model was trained by a comprehensive parameter uncertainty framework, including parameter sensitivity, optimization, and regionalization. The rooting model was corrected based on high-resolution river flowlines, as well the ascertained gauge locations and catchment areas. Supported by a well-trained model system, about 83% of the catchments across China exhibited NSE > 0.7, and about 56% of the catchments exhibited KGE > 0.7. The systematic bias of estimated natural streamflow from a calibrated land surface model was reduced by the statistical post-processing technique with the Pbias metric decreased from 17.13% to 2.27%. The reconstructed gauge-based streamflow dataset provides a reliable representation of natural hydrological processes in regions affected by intensive human activity.

File naming and required software

Filename: streamflow data are stored in ASCII files and one file per station. The naming convention follows the template 'xxx' (e.g. Haerbin) where 'xxx' is the English name for the station.
Data reading method: all ASCII files in the dataset can be opened directly with text programs (such as Notepad). Except for the header file, the main content is monthly streamflow data. The first column is the year, the second column is the month, and the third column is the streamflow (m3 s-1).

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Cite as:

Miao, C., Gou, J. (2021). China's high-quality natural streamflow gauge-based dataset (1961–2018). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Hydro.tpdc.271644. CSTR: 18406.11.Hydro.tpdc.271644. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Miao, C. Y., Gou, J. J., Fu, B. J., Tang, Q. H., Duan, Q. Y., Chen, Z. S., Lei, H. M., Chen, J., Guo, J. L., Borthwick, A. G. L., Ding, W. F., Duan, X. W., Li, Y. G., Kong, D. X., Guo, X. Y., Wu, J. W. (2021). High-quality reconstruction of China's natural streamflow. Science Bulletin. (Under Review)( View Details | Bibtex)

2. Gou, J. J., Miao, C. Y., Samaniego, L., Xiao, M., Wu, J. W. & Guo, X. Y. (2021). CNRD v1.0: a high-quality natural runoff dataset for hydrological and climate studies in China. Bulletin of the American Meteorological Society, 102(5), E929-E947.( View Details | Bibtex)

3. Gou, J. J., Miao, C. Y., Duan, Q. Y., Tang, Q. H., Di, Z. H., Liao, W. H., Wu, J. W. & Zhou, R. (2020). Sensitivity analysis-based automatic parameter calibration of the VIC model for streamflow simulations over China. Water Resources Research, 56: 1-19.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

The second comprehensive scientific investigation of Tibetan Plateau (No:2019QZKK0405)

National Natural Science Foundation of China (No. 41877155)

Copyright & License

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