Transforming global water cycle observations via synergistic AI and remote sensing.

Yao Z, Cui Y, Jin Z, Wu S, Guo Q, Xu Y, Guo Z, Jiang C, Qu Y, Zhai D, Fan W

DOI: 10.1126/sciadv.aef3610
Published: 2026 Jun 19
Container: Science advances
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1126/sciadv.aef3610,
  title = {Transforming global water cycle observations via synergistic AI and remote sensing.},
  author = {Yao Z and Cui Y and Jin Z and Wu S and Guo Q and Xu Y and Guo Z and Jiang C and Qu Y and Zhai D and Fan W},
  year = {2026},
  journal = {Science advances},
  doi = {10.1126/sciadv.aef3610},
  url = {https://doi.org/10.1126/sciadv.aef3610}
}

RIS

TY  - JOUR
TI  - Transforming global water cycle observations via synergistic AI and remote sensing.
AU  - Yao Z
AU  - Cui Y
AU  - Jin Z
AU  - Wu S
AU  - Guo Q
AU  - Xu Y
AU  - Guo Z
AU  - Jiang C
AU  - Qu Y
AU  - Zhai D
AU  - Fan W
PY  - 2026
JO  - Science advances
DO  - 10.1126/sciadv.aef3610
UR  - https://doi.org/10.1126/sciadv.aef3610
ER  -

APA

Z, Y., Y, C., Z, J., S, W., Q, G., Y, X., Z, G., C, J., Y, Q., D, Z., & W, F. (2026). Transforming global water cycle observations via synergistic AI and remote sensing.. Science advances. https://doi.org/10.1126/sciadv.aef3610

Source records

pubmed · retrieved 2026-09-25T07:56:03.856Z