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Machine learning downscaling of GRACE/GRACE-FO data to capture spatial-temporal drought effects on groundwater storage at a local scale under data-scarcity

Crossref DOI link: https://doi.org/10.1186/s40068-024-00368-1

Published Online: 2024-09-03

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Shilengwe, Christopher

Banda, Kawawa

Nyambe, Imasiku
Funding

Funding for this research was provided by:

Southern African Science Service Centre for Climate Change and Adaptive Land Management (Tipping Points Explained by Climate Change (TIPPECC) Project, Tipping Points Explained by Climate Change (TIPPECC) Project, Tipping Points Explained by Climate Change (TIPPECC) Project)
License Information

Text and Data Mining valid from 2024-09-03

Version of Record valid from 2024-09-03
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Article History

Received: 12 July 2024

Accepted: 17 August 2024

First Online: 3 September 2024

Declarations

:

: The authors declare no conflicts of interest.

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