An explainable AI approach to deciphering groundwater depth responses to climate variability and human activities in Western U.S.
- DOI
- 10.1016/j.scitotenv.2026.181852
- Published
- 2026-05-12
- Container
- Sci Total Environ
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.scitotenv.2026.181852,
title = {An explainable AI approach to deciphering groundwater depth responses to climate variability and human activities in Western U.S.},
author = {Dai Q and Siegel D and Xu T.},
year = {2026},
journal = {Sci Total Environ},
doi = {10.1016/j.scitotenv.2026.181852},
url = {https://doi.org/10.1016/j.scitotenv.2026.181852}
}RIS
TY - JOUR TI - An explainable AI approach to deciphering groundwater depth responses to climate variability and human activities in Western U.S. AU - Dai Q AU - Siegel D AU - Xu T. PY - 2026 JO - Sci Total Environ DO - 10.1016/j.scitotenv.2026.181852 UR - https://doi.org/10.1016/j.scitotenv.2026.181852 ER -
APA
Q, D., D, S., & T., X. (2026). An explainable AI approach to deciphering groundwater depth responses to climate variability and human activities in Western U.S.. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2026.181852
Source records
- europe-pmc · retrieved 2026-09-25T13:47:30.822Z