8 citations as recorded by crossref.

1. Is smart sampling worth it? Impact of training data selection on the performance of LSTMs in streamflow prediction B. Heudorfer & R. Loritz
2. A deep learning framework for mapping evergreen conifer fractional cover at 30 m resolution using fused bi-temporal WorldView and time-series Landsat imagery in mixed mountain forests X. Zhu et al.
3. HydroGRAF: Hybrid discharge reconstruction and basin-aware streamflow forecasting in the Himalayas A. Gul et al.
4. Evaluating rainfall-driven LSTM for statistical analysis of low-flow regimes in the Nakagawa basin, Japan D. Kim & N. Shirakawa
5. Streamflow prediction using an incremental attention network with LSTM and Chaos optimization techniques S. Apak et al.
6. How well do process-based and data-driven hydrological models learn from limited discharge data? M. Staudinger et al.
7. Landscape metrics selection and influence over hydrological signatures: land use change’s effect over water resources in Chile L. Henriquez-Dole et al.
8. An interpretable machine learning approach for alkalinity reconstruction in the Mediterranean Sea T. Tonelli et al.