11 citations as recorded by crossref.

1. Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework L. Zhou et al. 10.1016/j.jhydrol.2022.128843
2. Hydrological digital twin model of a large anthropized italian alpine catchment: The Adige river basin M. Morlot et al. 10.1016/j.jhydrol.2023.130587
3. RoGeR v3.0.5 – a process-based hydrological toolbox model in Python R. Schwemmle et al. 10.5194/gmd-17-5249-2024
4. Enhancing runoff simulation by combining superflex with deep learning methods in China's Qinghai Lake Basin, Northeast Tibetan Plateau K. Liu et al. 10.1016/j.ejrh.2025.102331
5. RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling R. Chlumsky et al. 10.5194/gmd-15-7017-2022
6. Why do we have so many different hydrological models? A review based on the case of Switzerland P. Horton et al. 10.1002/wat2.1574
7. Prediction of Qinghai Lake's level under future climate change: A hybrid modeling approach based on hydrological model and deep learning method K. Liu et al. 10.1016/j.ejrh.2025.102283
8. OpenForecast: An Assessment of the Operational Run in 2020–2021 G. Ayzel & D. Abramov 10.3390/geosciences12020067
9. HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists R. Rigon et al. 10.5194/hess-26-4773-2022
10. To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization E. Acuña Espinoza et al. 10.5194/hess-28-2705-2024
11. Exploring Signature‐Based Model Calibration for Streamflow Prediction in Ungauged Basins M. Dal Molin et al. 10.1029/2022WR031929