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.

Data sets

Landsat data U.S. Geological Survey and NASA https://cloud.google.com/storage/docs/public-datasets/landsat

Model code and software

CABLE: The Community Atmosphere Biosphere Land Exchange Model source code National Computational Infrastructure (NCI) https://trac.nci.org.au/trac/cable/

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.