Preprints
https://doi.org/10.5194/essd-2019-224
https://doi.org/10.5194/essd-2019-224
02 Jan 2020
 | 02 Jan 2020
Status: this preprint was under review for the journal ESSD. A final paper is not foreseen.

A dataset of distributed global water withdrawal from 1960 to 2017

Denghua Yan, Baisha Weng, Tianling Qin, Hao Wang, Xiangnan Li, Yuheng Yang, Kun Wang, Zhenyu Lv, Jianwei Wang, Meng Li, Shan He, Fang Liu, Shanshan Liu, Wuxia Bi, Ting Xu, Xiaoqing Shi, Zihao Man, Congwu Sun, Meiyu Liu, Mengke Wang, Yinghou Huang, Haoyu Long, Yongzhen Niu, Batsuren Dorjsuren, Mohammed Gedefaw, Abel Girma, and Asaminew Abiyu

Abstract. More and more high-resolution data sets are simulated worldwide and used in various research. However, in addition to the improvement in accuracy, the practical significance of the spatial distribution of data must also be considered. Considering that the most accurate water withdrawal data are mainly provided by the state, water is mainly concentrated on artificial surface and cultivated land. Whenever possible, using data published by regional or national governments and interpolating and extending them to specific land uses will maximize data accuracy. Based on this, we provide a set of water withdrawal intensity products from 1960 to 2017 distributed to the administrative units or the corresponding regions. The data set fills the gaps in the multi-year data set of the accurate intensity of water withdrawal. The datasets described in this article are publicly and freely available through the FigShare. The DOI for the data is https://doi.org/10.6084/m9.figshare.10012559.v1 (Yanetal.,2019).

This preprint has been withdrawn.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Denghua Yan, Baisha Weng, Tianling Qin, Hao Wang, Xiangnan Li, Yuheng Yang, Kun Wang, Zhenyu Lv, Jianwei Wang, Meng Li, Shan He, Fang Liu, Shanshan Liu, Wuxia Bi, Ting Xu, Xiaoqing Shi, Zihao Man, Congwu Sun, Meiyu Liu, Mengke Wang, Yinghou Huang, Haoyu Long, Yongzhen Niu, Batsuren Dorjsuren, Mohammed Gedefaw, Abel Girma, and Asaminew Abiyu

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Denghua Yan, Baisha Weng, Tianling Qin, Hao Wang, Xiangnan Li, Yuheng Yang, Kun Wang, Zhenyu Lv, Jianwei Wang, Meng Li, Shan He, Fang Liu, Shanshan Liu, Wuxia Bi, Ting Xu, Xiaoqing Shi, Zihao Man, Congwu Sun, Meiyu Liu, Mengke Wang, Yinghou Huang, Haoyu Long, Yongzhen Niu, Batsuren Dorjsuren, Mohammed Gedefaw, Abel Girma, and Asaminew Abiyu
Denghua Yan, Baisha Weng, Tianling Qin, Hao Wang, Xiangnan Li, Yuheng Yang, Kun Wang, Zhenyu Lv, Jianwei Wang, Meng Li, Shan He, Fang Liu, Shanshan Liu, Wuxia Bi, Ting Xu, Xiaoqing Shi, Zihao Man, Congwu Sun, Meiyu Liu, Mengke Wang, Yinghou Huang, Haoyu Long, Yongzhen Niu, Batsuren Dorjsuren, Mohammed Gedefaw, Abel Girma, and Asaminew Abiyu

Viewed

Total article views: 2,238 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,787 357 94 2,238 111 128
  • HTML: 1,787
  • PDF: 357
  • XML: 94
  • Total: 2,238
  • BibTeX: 111
  • EndNote: 128
Views and downloads (calculated since 02 Jan 2020)
Cumulative views and downloads (calculated since 02 Jan 2020)

Viewed (geographical distribution)

Total article views: 2,131 (including HTML, PDF, and XML) Thereof 2,112 with geography defined and 19 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 Nov 2024
Download

This preprint has been withdrawn.

Short summary
This paper provides a complete data set of global water withdrawal. There is almost no continuous long series of water withdrawal data globally. Moreover, most of the data released by international organizations is based on national scale and lacks finer regional data. Therefore, appropriate methods are needed to modify the data. This dataset has important practical significance in promoting the harmonious and sustainable development of economy and resources of the world.
Altmetrics