7 citations as recorded by crossref.

1. Research on Provincial-Level Soil Moisture Prediction Based on Extreme Gradient Boosting Model Y. Ren et al. https://doi.org/10.3390/agriculture13050927
2. Innovative approach for estimating evapotranspiration and gross primary productivity by integrating land data assimilation, machine learning, and multi-source observations X. He et al. https://doi.org/10.1016/j.agrformet.2024.110136
3. Improving soil moisture simulation by optimizing soil texture profiles with a micro-genetic algorithm S. Lim et al. https://doi.org/10.1016/j.envsoft.2025.106754
4. Dynamic Assimilation of Deep Learning Predictions to a Process-Based Water Budget N. Martin https://doi.org/10.3390/hydrology10060129
5. A new approach for joint assimilation of cosmic-ray neutron soil moisture and groundwater level data into an integrated terrestrial model F. Li et al. https://doi.org/10.5194/hess-29-6419-2025
6. Field scale computer modeling of soil moisture with dynamic nudging assimilation algorithm O. Kozhushko et al. https://doi.org/10.23939/mmc2022.02.203
7. Water Resources’ AI–ML Data Uncertainty Risk and Mitigation Using Data Assimilation N. Martin & J. White https://doi.org/10.3390/w16192758