Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 24, issue 11
Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5251-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-5251-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 11
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, Kasper Johansen, Bruno José Luis Aragón Solorio, Ting Li, Rasmus Houborg, Yoann Malbeteau, Samer AlMashharawi, Muhammad Umer Altaf, Essam Mohammed Fallatah, Hari Prasad Dasari, Ibrahim Hoteit, and Matthew Francis McCabe

Viewed

Total article views: 6,306 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
4,474 1,721 111 6,306 183 134 135
  • HTML: 4,474
  • PDF: 1,721
  • XML: 111
  • Total: 6,306
  • Supplement: 183
  • BibTeX: 134
  • EndNote: 135
Views and downloads (calculated since 25 Feb 2020)
Cumulative views and downloads (calculated since 25 Feb 2020)

Viewed (geographical distribution)

Total article views: 6,306 (including HTML, PDF, and XML) Thereof 5,792 with geography defined and 514 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 16 Nov 2025
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.
Read more
Share