The post-processing spatial and temporal distribution of water resources (runoff) in the Tibet Plateau from 2046 to 2065

The post-processing spatial and temporal distribution of water resources (runoff) in the Tibet Plateau from 2046 to 2065

The basic data of hydrometeorology, land use and DEM were collected through the National Meteorological Information Center, the Hydrological Yearbook, the China Statistical Yearbook and the Institute of Geographic Sciences and Resources of the Chinese Academy of Sciences. The distributed time-varying gain hydrological model with independent intellectual property rights is used for modeling, and the Qinghai Tibet Plateau is divided into 10937 sub basins with a threshold of 100 square kilometers. In Heihe River, Yarlung Zangbo River, the source of Yangtze River, the source of Yellow River, Yalong River, Minjiang River and Lancang River basins, 14 flow stations were selected to observe the daily flow data to develop and verify the model. The daily scale Naxi efficiency coefficient is above 0.7, and the correlation coefficient is above 0.8. The precipitation and temperature data output from 13 models and 4 scenarios provided by CMIP6 are used to post process the future precipitation and temperature data. The post processed precipitation and temperature driven hydrological model simulates the water cycle process from 2046 to 2065, and gives the possible future spatial and temporal distribution of 0.1 degree daily scale runoff across the Qinghai Tibet Plateau.

File naming and required software

1 NetCdf file for each scenario and model

Data Citations Data citation guideline What's data citation?
Cite as:

Ye, A. (2022). The post-processing spatial and temporal distribution of water resources (runoff) in the Tibet Plateau from 2046 to 2065. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Terre.tpdc.272895. CSTR: 18406.11.Terre.tpdc.272895. (Download the reference: RIS | Bibtex )

Related Literatures:

1. Xia, J., Wang, G.S., Tan, G., Ye, A.Z., & Huang, G.H. (2005). Development of distributed time-variant gain model for nonlinear hydrological systems. Science in china series d:earth sciences, 48(6), 713-723.( View Details | Bibtex)

2. Ye, A., Duan, Q., Zeng, H., Li, L., & Wang, C. (2010). A Distributed Time—Variant Gain Hydrological Model Based on Remote Sensing. Journal of Resources and Ecology, 1, 222-30.( View Details | Bibtex)

3. Wang, Y., Ye, A*., Peng, D., Miao, C., Di, Z., & Gong, W. (2022). Spatiotemporal variations in water conservation function of the Tibetan Plateau under climate change based on InVEST model. Journal of Hydrology: Regional Studies, 41, 101064.( 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

CASEarth:Big Earth Data for Three Poles(grant No. XDA19070000) (No:XDA19000000)

the Strategic Priority Research Program of the Chinese Academy of Sciences (No:XDA19070104) [XDA19070104]

Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

License: This work is licensed under an Attribution 4.0 International (CC BY 4.0)

Related Resources

Current page automatically show English comments Show comments in all languages

Download Follow
Geographic coverage
East: 105.00 West: 70.00
South: 40.00 North: 25.00
  • Temporal resolution: Daily
  • Spatial resolution: 1km - 10km
  • File size: 90,000 MB
  • Views: 2,010
  • Downloads: 29
  • Access: Open Access
  • Temporal coverage: 2046-01-01 To 2065-12-31
  • Updated time: 2022-11-04
: YE Aizhong  

Distributor: A Big Earth Data Platform for Three Poles


Export metadata