7 citations as recorded by crossref.

1. A Machine Learning approach for Total Water storage anomaly eXtension back to 1980 (ML-TWiX) P. Saemian et al. https://doi.org/10.1038/s41597-026-06604-w
2. Multidecadal reconstruction of terrestrial water storage changes by combining pre-GRACE satellite observations and climate data C. Hacker et al. https://doi.org/10.5194/essd-18-1747-2026
3. Attributing terrestrial water storage changes on the Tibetan Plateau to climate and human drivers using a hybrid deep learning approach Z. Yang et al. https://doi.org/10.1016/j.jhydrol.2026.135599
4. Spatial-temporal dynamics of meteorological and groundwater drought in Northwest China: Propagation, threshold, recovery time, drivers J. Shan et al. https://doi.org/10.1016/j.ejrh.2025.103090
5. Retrievals and simulations of terrestrial water storage changes and runoff over the Tibetan Plateau: Challenges and opportunities X. Li et al. https://doi.org/10.1016/j.fmre.2025.11.012
6. Enhancing water science in Earth’s second lung: AI-generated centenary hydrological insights from two decades of satellite data in the Congo Basin J. Awange & J. Wang https://doi.org/10.1016/j.srs.2026.100402
7. Groundwater Storage Variations in the Huadian Photovoltaic Base of the Tengger Desert Based on Machine Learning–Downscaled GRACE Data R. Chen et al. https://doi.org/10.3390/w18070781