90 citations as recorded by crossref.

1. Improving Operational Short- to Medium-Range (SR2MR) Streamflow Forecasts in the Upper Zambezi Basin and Its Sub-Basins Using Variational Ensemble Forecasting R. Valdés-Pineda et al. 10.3390/hydrology8040188
2. Exploratory analysis of statistical post‐processing methods for hydrological ensemble forecasts M. Boucher et al. 10.1002/hyp.10234
3. Parameter dimensionality reduction of a conceptual model for streamflow prediction in Canadian, snowmelt dominated ungauged basins R. Arsenault et al. 10.1016/j.advwatres.2015.08.014
4. Measurement and Partitioning of Evapotranspiration for Application to Vadose Zone Studies R. Anderson et al. 10.2136/vzj2017.08.0155
5. Generating Coherent Ensemble Forecasts After Hydrological Postprocessing: Adaptations of ECC‐Based Methods J. Bellier et al. 10.1029/2018WR022601
6. Application of weather post-processing methods for operational ensemble hydrological forecasting on multiple catchments in Canada F. Aguilar Andrade et al. 10.1016/j.jhydrol.2024.131861
7. Predicting lymphatic filariasis transmission and elimination dynamics using a multi-model ensemble framework M. Smith et al. 10.1016/j.epidem.2017.02.006
8. Comparison of Deterministic and Probabilistic Variational Data Assimilation Methods Using Snow and Streamflow Data Coupled in HBV Model for Upper Euphrates Basin G. Uysal et al. 10.3390/geosciences13030089
9. Suitability of Global Circulation Model Downscaled BCCA Daily Precipitation for Local Hydrologic Applications R. Gyawali et al. 10.1061/(ASCE)HE.1943-5584.0001452
10. A multimodel data assimilation framework via the ensemble Kalman filter L. Xue & D. Zhang 10.1002/2013WR014525
11. The Science of NOAA's Operational Hydrologic Ensemble Forecast Service J. Demargne et al. 10.1175/BAMS-D-12-00081.1
12. Improving multi-model ensemble streamflow forecasts by combining lumped, distributed and deep learning hydrological models W. Armstrong et al. 10.1080/02626667.2025.2471430
13. Accounting for three sources of uncertainty in ensemble hydrological forecasting A. Thiboult et al. 10.5194/hess-20-1809-2016
14. Large-sample study of uncertainty of hydrological model components over North America M. Troin et al. 10.1016/j.jhydrol.2022.127766
15. <i>Preface</i> Towards practical applications in ensemble hydro-meteorological forecasting Y. He et al. 10.5194/adgeo-29-119-2011
16. How do potential evapotranspiration formulas influence hydrological projections? G. Seiller & F. Anctil 10.1080/02626667.2015.1100302
17. Long-term inflow forecast using meteorological data based on long short-term memory neural networks H. Zhao et al. 10.2166/hydro.2024.196
18. Comparison and integration of hydrological models and machine learning models in global monthly streamflow simulation J. Zhang et al. 10.1016/j.jhydrol.2024.132549
19. Benchmarking hydrological models for low-flow simulation and forecasting on French catchments P. Nicolle et al. 10.5194/hess-18-2829-2014
20. Ensemble flood forecasting considering dominant runoff processes – Part 1: Set-up and application to nested basins (Emme, Switzerland) M. Antonetti et al. 10.5194/nhess-19-19-2019
21. MultiRain: a GIS-based tool for multi-model estimation of regional design rainfall for scientists and practitioners S. Grasso et al. 10.2166/hydro.2019.016
22. Hydrological ensemble forecasting using a multi-model framework P. Dion et al. 10.1016/j.jhydrol.2021.126537
23. Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems E. Valdez et al. 10.5194/hess-26-197-2022
24. HESS Opinions "Forecaster priorities for improving probabilistic flood forecasts" F. Wetterhall et al. 10.5194/hess-17-4389-2013
25. On the difficulty to optimally implement the Ensemble Kalman filter: An experiment based on many hydrological models and catchments A. Thiboult & F. Anctil 10.1016/j.jhydrol.2015.09.036
26. Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
27. Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil F. Fan et al. 10.1016/j.ejrh.2015.05.012
28. Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 1: Optimization criteria D. Brochero et al. 10.5194/hess-15-3307-2011
29. Multi-model approach in a variable spatial framework for streamflow simulation C. Thébault et al. 10.5194/hess-28-1539-2024
30. Investigating hydrological model versatility to simulate extreme flood events D. Peredo et al. 10.1080/02626667.2022.2030864
31. Enhancing the predictability of flood forecasts by combining Numerical Weather Prediction ensembles with multiple hydrological models K. Nikhil Teja et al. 10.1016/j.jhydrol.2023.130176
32. Performance and Reliability of Probabilistic Scenarios of Interpolated Rainfall Based on Geostatistics H. Razafimahefa & F. Anctil 10.1061/(ASCE)HE.1943-5584.0000913
33. Improving the predictive skills of hydrological models using a combinatorial optimization algorithm and artificial neural networks J. Farfán & L. Cea 10.1007/s40808-022-01540-1
34. Evaluation of hydroclimatic biases in the Community Earth System Model (CESM1) within the Mississippi River basin M. O'Donnell et al. 10.5194/hess-29-4637-2025
35. Impact of climate change on the vulnerability of drinking water intakes in a northern region B. Leveque et al. 10.1016/j.scs.2020.102656
36. A semi‐empirical wind set‐up forecasting model for Lake Champlain G. Loiselle et al. 10.1002/hyp.14240
37. Performance Evaluation of Homogeneous and Heterogeneous Ensemble Models for Groundwater Salinity Predictions: a Regional-Scale Comparison Study A. Lal & B. Datta 10.1007/s11270-020-04693-w
38. Sub-seasonal streamflow forecasts for hydropower dams in the Brazilian Eletrical Interconnected System E. Quedi et al. 10.1590/2318-0331.292420230109
39. An Efficient Method to Correct Under-Dispersion in Ensemble Streamflow Prediction of Inflow Volumes for Reservoir Optimization R. Arsenault et al. 10.1007/s11269-016-1425-4
40. Performance dependence of multi-model combination methods on hydrological model calibration strategy and ensemble size Y. Wan et al. 10.1016/j.jhydrol.2021.127065
41. Real-time hydrograph modelling in the upper Nysa Kłodzka river basin (SW Poland): a two-model hydrologic ensemble prediction approach T. Niedzielski & B. Miziński 10.1007/s00477-016-1251-5
42. Aplicación de técnicas de “time-lagged ensembles” al pronóstico de precipitación del modelo GEFS en una cuenca hidroeléctrica A. De Vera & R. Terra 10.1080/23863781.2025.2541575
43. Ensemble forecasting system for the management of the Senegal River discharge: application upstream the Manantali dam D. Ndione et al. 10.1007/s13201-020-01199-y
44. Hydrostreamer v1.0 – improved streamflow predictions for local applications from an ensemble of downscaled global runoff products M. Kallio et al. 10.5194/gmd-14-5155-2021
45. Building a Multimodel Flood Prediction System with the TIGGE Archive E. Zsótér et al. 10.1175/JHM-D-15-0130.1
46. Data Assimilation for Streamflow Forecasting: State–Parameter Assimilation versus Output Assimilation L. Sun et al. 10.1061/(ASCE)HE.1943-5584.0001475
47. Assessment of Ensemble Flood Forecasting with Numerical Weather Prediction by considering Spatial Shift of Rainfall Fields W. Yu et al. 10.1007/s12205-018-0407-x
48. Potential skill of continental-scale, medium-range ensemble streamflow forecasts for flood prediction in South America V. Siqueira et al. 10.1016/j.jhydrol.2020.125430
49. Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II J. Xu et al. 10.5194/hess-26-1001-2022
50. Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model R. Montero et al. 10.1016/j.advwatres.2016.04.011
51. Strategies for hydrologic ensemble generation and calibration: On the merits of using model-based predictors A. Tiberi-Wadier et al. 10.1016/j.jhydrol.2021.126233
52. Integrating machine learning ensembles and flood classification for enhanced flood forecasting with dynamic parameter weighting H. Oppel et al. 10.2166/hydro.2025.030
53. Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness? D. Birhanu et al. 10.3390/su10082837
54. Technical review of large-scale hydrological models for implementation in operational flood forecasting schemes on continental level A. Kauffeldt et al. 10.1016/j.envsoft.2015.09.009
55. What can be expected from a semi-distributed multi-model approach for streamflow forecasting? Tailoring the structure and size of a super-ensemble on the Rhône basin C. Thébault et al. 10.1016/j.jhydrol.2025.133589
56. Multi-parametric variational data assimilation for hydrological forecasting R. Alvarado-Montero et al. 10.1016/j.advwatres.2017.09.026
57. Ensemble rainfall–runoff modeling of physically based semi-distributed models using multi-source rainfall data fusion T. Gichamo et al. 10.2166/wcc.2023.084
58. Ensemble Bayesian forecasting system Part II: Experiments and properties H. Herr & R. Krzysztofowicz 10.1016/j.jhydrol.2019.02.057
59. Statistical processing of forecasts for hydrological ensemble prediction: a comparative study of different bias correction strategies I. Zalachori et al. 10.5194/asr-8-135-2012
60. Assessment of models predicting anthropogenic interventions and climate variability on surface runoff of the Lower Zab River R. Mohammed et al. 10.1007/s00477-016-1375-7
61. Improving global hydrological simulations through bias-correction and multi-model blending A. Chevuturi et al. 10.1016/j.jhydrol.2023.129607
62. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model M. Demirel et al. 10.5194/hess-22-1299-2018
63. Dealing with uncertainty in ecosystem model scenarios: Application of the single-model ensemble approach G. Gal et al. 10.1016/j.envsoft.2014.05.015
64. A flood episode in northern Italy: multi-model and single-model mesoscale meteorological ensembles for hydrological predictions S. Davolio et al. 10.5194/hess-17-2107-2013
65. Quantifying multi-source uncertainties in multi-model predictions using the Bayesian model averaging scheme S. Jiang et al. 10.2166/nh.2017.272
66. Ensemble streamflow prediction considering the influence of reservoirs in Narmada River Basin, India U. Vegad & V. Mishra 10.5194/hess-26-6361-2022
67. Multi-parameter approaches for improved ensemble prediction accuracy in hydrology and water quality modeling S. Shin et al. 10.1016/j.jhydrol.2023.129458
68. Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan N. Mount et al. 10.1080/02626667.2016.1159683
69. Transferability of hydrological models and ensemble averaging methods between contrasting climatic periods C. Broderick et al. 10.1002/2016WR018850
70. Assimilation of water temperature and discharge data for ensemble water temperature forecasting S. Ouellet-Proulx et al. 10.1016/j.jhydrol.2017.09.027
71. Selecting components in a probabilistic hydrological forecasting chain: the benefits of an integrated evaluation J. Bellier et al. 10.1080/27678490.2021.1936825
72. Enhancing Low-Flow Forecasts: A Multi-Model Approach for Rainfall–Runoff Models C. Andraos 10.3390/hydrology11030035
73. Enhancing streamflow forecasting for the Brazilian electricity sector: a strategy based on a hyper-multimodel F. Souza Filho et al. 10.1590/2318-0331.282320230120
74. Streamflow prediction in ungauged basins: analysis of regionalization methods in a hydrologically heterogeneous region of Mexico R. Arsenault et al. 10.1080/02626667.2019.1639716
75. Simulating ecologically relevant hydrological indicators in a temporary river system A. De Girolamo et al. 10.1016/j.agwat.2016.05.034
76. Advancing Medium-Range Streamflow Forecasting for Large Hydropower Reservoirs in Brazil by Means of Continental-Scale Hydrological Modeling A. Kolling Neto et al. 10.3390/w15091693
77. Identification of Hydrological Models for Enhanced Ensemble Reservoir Inflow Forecasting in a Large Complex Prairie Watershed F. Awol et al. 10.3390/w11112201
78. Design and experimentation of an empirical multistructure framework for accurate, sharp and reliable hydrological ensembles G. Seiller et al. 10.1016/j.jhydrol.2017.07.002
79. Estimating storm runoff extreme in small ungauged catchments using an integrated modeling approach Z. Zhao et al. 10.1016/j.horiz.2024.100092
80. Inter-comparison between retrospective ensemble streamflow forecasts using meteorological inputs from ECMWF and NOAA/ESRL in the Hudson River sub-basins during Hurricane Irene (2011) F. Saleh et al. 10.2166/nh.2018.182
81. UAV-based emergency treatment plan for flood disasters at the Hongyanhe nuclear power plant Y. Ma et al. 10.1016/j.ecolind.2023.110676
82. Evaluation of the Impact of Multi-Source Uncertainties on Meteorological and Hydrological Ensemble Forecasting Z. Shu et al. 10.1016/j.eng.2022.06.007
83. Operational forecast uncertainty assessment for better information to stakeholders and crisis managers L. Berthet et al. 10.1051/e3sconf/20160718005
84. Simplifying a hydrological ensemble prediction system with a backward greedy selection of members – Part 2: Generalization in time and space D. Brochero et al. 10.5194/hess-15-3327-2011
85. MOHYSE – a simple lumped hydrological model for educational and research purposes J. Martel et al. 10.1080/07011784.2025.2536023
86. Uncertainty of Hydrological Model Components in Climate Change Studies over Two Nordic Quebec Catchments M. Troin et al. 10.1175/JHM-D-17-0002.1
87. Multi‐temporal Hydrological Residual Error Modeling for Seamless Subseasonal Streamflow Forecasting D. McInerney et al. 10.1029/2019WR026979
88. Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach M. Cassagnole et al. 10.5194/hess-25-1033-2021
89. Regional regression models for hydro‐climate change impact assessment R. Gyawali et al. 10.1002/hyp.10312
90. AI-driven morphoclimatic regional frequency modelling of sub-daily rainfall-extremes A. Magnini et al. 10.1016/j.jhydrol.2024.130808