Articles | Volume 24, issue 11
Hydrol. Earth Syst. Sci., 24, 5251–5277, 2020
https://doi.org/10.5194/hess-24-5251-2020
Hydrol. Earth Syst. Sci., 24, 5251–5277, 2020
https://doi.org/10.5194/hess-24-5251-2020
Research article
12 Nov 2020
Research article | 12 Nov 2020

Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach

Oliver Miguel López Valencia et al.

Viewed

Total article views: 4,017 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,871 1,104 42 4,017 105 32 39
  • HTML: 2,871
  • PDF: 1,104
  • XML: 42
  • Total: 4,017
  • Supplement: 105
  • BibTeX: 32
  • EndNote: 39
Views and downloads (calculated since 25 Feb 2020)
Cumulative views and downloads (calculated since 25 Feb 2020)

Viewed (geographical distribution)

Total article views: 4,017 (including HTML, PDF, and XML) Thereof 3,553 with geography defined and 464 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 30 Jan 2023
Download
Short summary
The agricultural sector in Saudi Arabia has expanded rapidly over the last few decades, supported by non-renewable groundwater abstraction. This study describes a novel data–model fusion approach to compile national-scale groundwater abstractions and demonstrates its use over 5000 individual center-pivot fields. This method will allow both farmers and water management agencies to make informed water accounting decisions across multiple spatial and temporal scales.