46 citations as recorded by crossref.

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2. A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes J. Quilty & J. Adamowski https://doi.org/10.1016/j.envsoft.2020.104718
3. Ensemble Streamflow Forecasting across the U.S. Mid-Atlantic Region with a Distributed Hydrological Model Forced by GEFS Reforecasts R. Siddique & A. Mejia https://doi.org/10.1175/JHM-D-16-0243.1
4. Validation and Bias Correction of Forecast Reference Evapotranspiration for Agricultural Applications in Nevada D. McEvoy et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0001595
5. Water Temperature Ensemble Forecasts: Implementation Using the CEQUEAU Model on Two Contrasted River Systems S. Ouellet-Proulx et al. https://doi.org/10.3390/w9070457
6. Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. https://doi.org/10.1029/2020WR028392
7. Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil F. Fan et al. https://doi.org/10.1016/j.ejrh.2015.05.012
8. A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin F. Saleh et al. https://doi.org/10.5194/hess-20-2649-2016
9. A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques F. Chang & M. Tsai https://doi.org/10.1016/j.jhydrol.2016.01.056
10. Assimilation of water temperature and discharge data for ensemble water temperature forecasting S. Ouellet-Proulx et al. https://doi.org/10.1016/j.jhydrol.2017.09.027
11. Evaluation of upper Uruguay river basin (Brazil) operational flood forecasts F. Fan et al. https://doi.org/10.1590/2318-0331.0217160027
12. An Ensemble-Based Analysis of a Liminal Extreme Rainfall Event near Taiwan A. Cole et al. https://doi.org/10.3390/atmos13071011
13. Hydrological post-processing of streamflow forecasts issued from multimodel ensemble prediction systems J. Xu et al. https://doi.org/10.1016/j.jhydrol.2019.124002
14. Introducing time series features based dynamic weights estimation framework for hydrologic forecast merging M. Sheikh & P. Coulibaly https://doi.org/10.1016/j.jhydrol.2025.132872
15. 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. https://doi.org/10.1016/j.jhydrol.2025.133589
16. A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations A. Sikorska-Senoner & J. Quilty https://doi.org/10.1016/j.envsoft.2021.105094
17. Postprocessing of Ensemble Weather Forecasts Using a Stochastic Weather Generator J. Chen et al. https://doi.org/10.1175/MWR-D-13-00180.1
18. Forecasting point-of-consumption chlorine residual in refugee settlements using ensembles of artificial neural networks M. De Santi et al. https://doi.org/10.1038/s41545-021-00125-2
19. Uncertainty analysis of machine learning models for SPEI estimation in the Persian Gulf and Caspian Sea M. Mohammadi et al. https://doi.org/10.1007/s11069-025-07539-y
20. An Ensemble Flow Forecast Method Based on Autoregressive Model and Hydrological Uncertainty Processer X. Yang et al. https://doi.org/10.3390/w12113138
21. Ensemble‐Based Neural Network Modeling for Hydrologic Forecasts: Addressing Uncertainty in the Model Structure and Input Variable Selection T. Kim et al. https://doi.org/10.1029/2019WR026262
22. Short-Term Reservoir Optimization for Flood Mitigation under Meteorological and Hydrological Forecast Uncertainty D. Schwanenberg et al. https://doi.org/10.1007/s11269-014-0899-1
23. How much does a high-resolution global ensemble forecast improve upon deterministic prediction skill for the Indian summer monsoon? P. Chakraborty et al. https://doi.org/10.1007/s00703-023-00966-1
24. Introducing entropy-based Bayesian model averaging for streamflow forecast P. Darbandsari & P. Coulibaly https://doi.org/10.1016/j.jhydrol.2020.125577
25. Water budget, performance of evapotranspiration formulations, and their impact on hydrological modeling of a small boreal peatland-dominated watershed P. Isabelle et al. https://doi.org/10.1139/cjes-2017-0046
26. Combining Stochastic Weather Generation and Ensemble Weather Forecasts for Short-Term Streamflow Prediction J. Chen & F. Brissette https://doi.org/10.1007/s11269-015-1001-3
27. Improving Flood Forecasting Skill by Combining Ensemble Precipitation Forecasts and Multiple Hydrological Models in a Mountainous Basin Y. Xiang et al. https://doi.org/10.3390/w16131887
28. Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach M. Cassagnole et al. https://doi.org/10.5194/hess-25-1033-2021
29. Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models H. Liu et al. https://doi.org/10.1002/hyp.14410
30. Combining Postprocessed Ensemble Weather Forecasts and Multiple Hydrological Models for Ensemble Streamflow Predictions J. Zhang et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001871
31. Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II J. Xu et al. https://doi.org/10.5194/hess-26-1001-2022
32. An Atmospheric–Hydrologic Forecasting Scheme for the Indus River Basin K. Shrestha et al. https://doi.org/10.1175/JHM-D-13-051.1
33. Western disturbances and climate variability: a review of recent developments K. Hunt et al. https://doi.org/10.5194/wcd-6-43-2025
34. Ensemble Based Forecasting and Optimization Framework to Optimize Releases from Water Supply Reservoirs for Flood Control V. Ramaswamy & F. Saleh https://doi.org/10.1007/s11269-019-02481-8
35. A Comparison of the Canadian Global and Regional Meteorological Ensemble Prediction Systems for Short-Term Hydrological Forecasting M. Abaza et al. https://doi.org/10.1175/MWR-D-12-00206.1
36. Impacts of precipitation uncertainty on hydrological ensemble simulations over the Ganjiang River basin X. Han & H. Yuan https://doi.org/10.1016/j.ejrh.2023.101617
37. Operational river discharge forecasting in poorly gauged basins: the Kavango River basin case study P. Bauer-Gottwein et al. https://doi.org/10.5194/hess-19-1469-2015
38. <i>Preface</i> Towards practical applications in ensemble hydro-meteorological forecasting Y. He et al. https://doi.org/10.5194/adgeo-29-119-2011
39. Hydro-economic assessment of hydrological forecasting systems M. Boucher et al. https://doi.org/10.1016/j.jhydrol.2011.11.042
40. Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment S. Jha et al. https://doi.org/10.5194/hess-22-1957-2018
41. Which precipitation forecasts to use? Deterministic versus coarser‐resolution ensemble NWP models P. Zhao et al. https://doi.org/10.1002/qj.3952
42. A sequential ensemble smoother for multiple data assimilation in hydrogeological modeling T. Béraud et al. https://doi.org/10.3389/frwa.2024.1462914
43. Value of various elements of the hydrological forecasting chain: Is there a successful pathway for improving the overall performance? J. Davidson-Chaput et al. https://doi.org/10.1016/j.jhydrol.2025.133186
44. An Efficient Method to Correct Under-Dispersion in Ensemble Streamflow Prediction of Inflow Volumes for Reservoir Optimization R. Arsenault et al. https://doi.org/10.1007/s11269-016-1425-4
45. Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. https://doi.org/10.3390/w16101438
46. Sub seasonal streamflow forecast assessment at large-scale basins E. Schmitt Quedi & F. Mainardi Fan https://doi.org/10.1016/j.jhydrol.2020.124635