11 citations as recorded by crossref.

1. Bridging gaps in ocean current modelling: a hybrid physics-driven deep learning approach P. Chang et al. https://doi.org/10.1080/20964471.2025.2603809
2. Filamentogenesis and Filamentolysis of a Low-Density Filament: Dynamic Processes in the Near-Surface Ocean Under Tidal Forcing M. Albinus et al. https://doi.org/10.5194/os-22-2143-2026
3. Adapting the effective flow work method for monopile scour estimation under combined wave-current loading M. Hoballah Jalloul et al. https://doi.org/10.1016/j.oceaneng.2026.126442
4. Using surface drifters to characterise near-surface ocean dynamics in the southern North Sea: a data-driven approach J. Medina-Rubio et al. https://doi.org/10.5194/os-22-49-2026
5. Sensor Technologies for Water Velocity, Flow, and Wave Motion Measurement in Marine Environments: A Comprehensive Review T. Matos https://doi.org/10.3390/jmse14040365
6. Simulation Study of the Effect of Multi-Angle ATI-SAR on Sea Surface Current Retrieval Accuracy J. Chen et al. https://doi.org/10.3390/rs17193383
7. Design and development of a low-cost GNSS-tracked surface drifter for investigating tidal currents in a creek environment V. Teppala et al. https://doi.org/10.1016/j.ecss.2024.109063
8. Transport and retention characteristics of floating debris in the Han River Estuary H. Do et al. https://doi.org/10.1016/j.marpolbul.2025.118670
9. Thermal Recovery Dynamics of the Ocean’s Cool-Skin Layer After Complete Mixing L. Jaeger et al. https://doi.org/10.16993/tellusa.4103
10. Review on renewable energy systems of unmanned marine vehicles and guidance for energy selection G. Wang et al. https://doi.org/10.1016/j.rser.2025.116085
11. Physics-informed neural networks to reconstruct surface velocity field from drifter data C. Bang et al. https://doi.org/10.3389/fmars.2025.1547995