30 citations as recorded by crossref.

1. Ensemble flood forecasting based on operational forecasts of the regional Eta EPS in the Taquari-Antas basin V. Siqueira et al. 10.1590/2318-0331.011616004
2. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios N. Addor et al. 10.5194/hess-15-2327-2011
3. Evaluation of Quantitative Precipitation Predictions by ECMWF, CMA, and UKMO for Flood Forecasting: Application to Two Basins in China Q. Ran et al. 10.1061/(ASCE)NH.1527-6996.0000282
4. Ensemble streamflow forecasting experiments in a tropical basin: The São Francisco river case study F. Fan et al. 10.1016/j.jhydrol.2014.04.038
5. Spatial Disaggregation of Mean Areal Rainfall Using Gibbs Sampling P. Gagnon et al. 10.1175/JHM-D-11-034.1
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7. Generative deep learning for probabilistic streamflow forecasting: Conditional variational auto-encoder M. Jahangir & J. Quilty 10.1016/j.jhydrol.2023.130498
8. Assessment of a multimodel ensemble against an operational hydrological forecasting system A. Thiboult & F. Anctil 10.1080/07011784.2015.1026402
9. Improved Spring Peak-Flow Forecasting Using Ensemble Meteorological Predictions S. Ahmed et al. 10.1061/(ASCE)HE.1943-5584.0001014
10. Sensitivity of hydrological ensemble forecasts to different sources and temporal resolutions of probabilistic quantitative precipitation forecasts: flash flood case studies in the Cévennes‐Vivarais region (Southern France) R. Marty et al. 10.1002/hyp.9543
11. Multi-model skill assessment of seasonal temperature and precipitation forecasts over Europe N. Mishra et al. 10.1007/s00382-018-4404-z
12. 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
13. A Comparative Study of Multi-Model Ensemble Forecasting Accuracy between Equal- and Variant-Weight Techniques X. Wei et al. 10.3390/atmos13040526
14. A cost-effective redundant communication system for improving the reliability of a flood early warning system E. López et al. 10.2166/hydro.2020.216
15. Ensemble‐Based Neural Network Modeling for Hydrologic Forecasts: Addressing Uncertainty in the Model Structure and Input Variable Selection T. Kim et al. 10.1029/2019WR026262
16. Combining Stochastic Weather Generation and Ensemble Weather Forecasts for Short-Term Streamflow Prediction J. Chen & F. Brissette 10.1007/s11269-015-1001-3
17. Short- and mid-term forecasts of actual evapotranspiration with deep learning E. Babaeian et al. 10.1016/j.jhydrol.2022.128078
18. Ensemble hydrological predictions at an intraseasonal scale through a statistical–dynamical downscaling approach over southwestern Amazonia W. Gomes et al. 10.2166/wcc.2024.262
19. Short-Term Reservoir Optimization for Flood Mitigation under Meteorological and Hydrological Forecast Uncertainty D. Schwanenberg et al. 10.1007/s11269-014-0899-1
20. Impacts of precipitation uncertainty on hydrological ensemble simulations over the Ganjiang River basin X. Han & H. Yuan 10.1016/j.ejrh.2023.101617
21. A comparison between ensemble and deterministic hydrological forecasts in an operational context M. Boucher et al. 10.5194/adgeo-29-85-2011
22. A Comparison of the Canadian Global and Regional Meteorological Ensemble Prediction Systems for Short-Term Hydrological Forecasting M. Abaza et al. 10.1175/MWR-D-12-00206.1
23. Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
24. Sequential streamflow assimilation for short-term hydrological ensemble forecasting M. Abaza et al. 10.1016/j.jhydrol.2014.08.038
25. Parameter-state ensemble thinning for short-term hydrological prediction B. Davison et al. 10.5194/hess-23-741-2019
26. Accelerated hydrological cycle on the Tibetan Plateau evidenced by ensemble modeling of Long-term water budgets Y. Wang et al. 10.1016/j.jhydrol.2022.128710
27. Hydrological post-processing of streamflow forecasts issued from multimodel ensemble prediction systems J. Xu et al. 10.1016/j.jhydrol.2019.124002
28. Time-series analysis with smoothed Convolutional Neural Network A. Wibawa et al. 10.1186/s40537-022-00599-y
29. An experiment on the evolution of an ensemble of neural networks for streamflow forecasting M. Boucher et al. 10.5194/hess-14-603-2010
30. 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