44 citations as recorded by crossref.

1. Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti R. Bathelemy et al. 10.5194/essd-16-2073-2024
2. Disentangling coastal groundwater level dynamics in a global dataset A. Nolte et al. 10.5194/hess-28-1215-2024
3. A Weak-Coupling Flow-Power Forecasting Method for Small Hydropower Station Group B. Chen et al. 10.1155/2023/1214269
4. A framework on utilizing of publicly availability stream gauges datasets and deep learning in estimating monthly basin-scale runoff in ungauged regions M. Le et al. 10.1016/j.advwatres.2024.104694
5. On the Evaluation of Both Spatial and Temporal Performance of Distributed Hydrological Models Using Remote Sensing Products T. Nguyen et al. 10.3390/rs14091959
6. Vorhersage von hydrologischen Abflusskennwerten in unbeobachteten Einzugsgebieten mit Machine Learning C. Klingler et al. 10.1007/s00506-022-00891-4
7. A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting G. Papacharalampous & H. Tyralis 10.3389/frwa.2022.961954
8. Temporal Fusion Transformers for streamflow Prediction: Value of combining attention with recurrence S. Rasiya Koya & T. Roy 10.1016/j.jhydrol.2024.131301
9. Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface H. McMillan et al. 10.1002/hyp.14481
10. A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022) X. Chen et al. 10.5194/essd-15-4463-2023
11. EStreams: An integrated dataset and catalogue of streamflow, hydro-climatic and landscape variables for Europe T. do Nascimento et al. 10.1038/s41597-024-03706-1
12. AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods A. Abbas et al. 10.5194/gmd-15-3021-2022
13. A dataset of lake-catchment characteristics for the Tibetan Plateau J. Liu et al. 10.5194/essd-14-3791-2022
14. Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale G. Papacharalampous et al. 10.1016/j.gsf.2022.101349
15. Where should hydrology go? An early-career perspective on the next IAHS Scientific Decade: 2023–2032 T. van Hateren et al. 10.1080/02626667.2023.2170754
16. FOCA: a new quality-controlled database of floods and catchment descriptors in Italy P. Claps et al. 10.5194/essd-16-1503-2024
17. BULL Database – Spanish Basin attributes for Unravelling Learning in Large-sample hydrology J. Senent-Aparicio et al. 10.1038/s41597-024-03594-5
18. Multi-model hydrological reference dataset over continental Europe and an African basin B. Droppers et al. 10.1038/s41597-024-03825-9
19. Large Scale Evaluation of Relationships Between Hydrologic Signatures and Processes H. McMillan et al. 10.1029/2021WR031751
20. A novel statistical-dynamical method for a seasonal forecast of particular matter in South Korea J. Jeong et al. 10.1016/j.scitotenv.2022.157699
21. Quantifying the Geomorphic Effect of Floods Using Satellite Observations of River Mobility A. Leenman et al. 10.1029/2023GL103875
22. Temporal hydrological drought clustering varies with climate and land-surface processes M. Brunner & K. Stahl 10.1088/1748-9326/acb8ca
23. A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies Z. Yin et al. 10.5194/essd-16-1559-2024
24. Influence of irrigation on root zone storage capacity estimation F. van Oorschot et al. 10.5194/hess-28-2313-2024
25. LamaH-Ice: LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland H. Helgason & B. Nijssen 10.5194/essd-16-2741-2024
26. Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters L. Bouaziz et al. 10.5194/hess-26-1295-2022
27. Deep learning for cross-region streamflow and flood forecasting at a global scale B. Zhang et al. 10.1016/j.xinn.2024.100617
28. Evaluation of satellite precipitation products for water allocation studies in the Sio-Malaba-Malakisi river basin of East Africa P. Omonge et al. 10.1016/j.ejrh.2021.100983
29. Lateral terrestrial water fluxes in the LSM of WRF‐Hydro: Benefits of a 2D groundwater representation T. Rummler et al. 10.1002/hyp.14510
30. Building Cross-Site and Cross-Network collaborations in critical zone science B. Arora et al. 10.1016/j.jhydrol.2023.129248
31. Res-CN (Reservoir dataset in China): hydrometeorological time series and landscape attributes across 3254 Chinese reservoirs Y. Shen et al. 10.5194/essd-15-2781-2023
32. CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland M. Höge et al. 10.5194/essd-15-5755-2023
33. Caravan - A global community dataset for large-sample hydrology F. Kratzert et al. 10.1038/s41597-023-01975-w
34. Widespread deoxygenation in warming rivers W. Zhi et al. 10.1038/s41558-023-01793-3
35. Setting expectations for hydrologic model performance with an ensemble of simple benchmarks W. Knoben 10.1002/hyp.15288
36. Global patterns in vegetation accessible subsurface water storage emerge from spatially varying importance of individual drivers F. van Oorschot et al. 10.1088/1748-9326/ad8805
37. Changes in the water retention of mountainous landscapes since the 1820s in the Austrian Alps G. Stecher et al. 10.3389/fenvs.2023.1219030
38. Uncertainty in Environmental Micropollutant Modeling H. Ahkola et al. 10.1007/s00267-024-01989-z
39. Potenzial von Machine Learning bei der kurzfristigen Leistungsprognose innerhalb einer Laufkraftwerkskette C. Klingler et al. 10.1007/s00506-022-00849-6
40. QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany P. Ebeling et al. 10.5194/essd-14-3715-2022
41. Catchment characterization: Current descriptors, knowledge gaps and future opportunities L. Tarasova et al. 10.1016/j.earscirev.2024.104739
42. Large-sample hydrology – a few camels or a whole caravan? F. Clerc-Schwarzenbach et al. 10.5194/hess-28-4219-2024
43. Vorhersage der Fließgewässertemperaturen in österreichischen Einzugsgebieten mittels Machine Learning-Verfahren M. Feigl et al. 10.1007/s00506-021-00771-3
44. LamaH | Large-Sample Data for Hydrology: Big data für die Hydrologie und Umweltwissenschaften C. Klingler et al. 10.1007/s00506-021-00769-x