58 citations as recorded by crossref.

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9. Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation R. Sun et al. https://doi.org/10.1016/j.jhydrol.2017.09.041
10. Enhancing probabilistic hydrological predictions with mixture density Networks: Accounting for heteroscedasticity and Non-Gaussianity D. Li et al. https://doi.org/10.1016/j.jhydrol.2024.131737
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19. System response curve correction method of runoff error for real-time flood forecast Q. Li et al. https://doi.org/10.2166/nh.2020.048
20. An automatic quality evaluation procedure for third-party daily rainfall observations and its application over Australia M. Li et al. https://doi.org/10.1007/s00477-023-02401-8
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22. Short-Term Streamflow and Flood Forecasting Based on Graph Convolutional Recurrent Neural Network and Residual Error Learning X. Pan et al. https://doi.org/10.1061/JCCEE5.CPENG-6757
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25. Quantifying the Risks that Propagate from the Inflow Forecast Uncertainty to the Reservoir Operations with Coupled Flood and Electricity Curtailment Risks Q. Ma et al. https://doi.org/10.3390/w13020173
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28. Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system S. Sharma et al. https://doi.org/10.5194/hess-22-1831-2018
29. 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
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34. Improving the Reliability of Sub‐Seasonal Forecasts of High and Low Flows by Using a Flow‐Dependent Nonparametric Model D. McInerney et al. https://doi.org/10.1029/2020WR029317
35. Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods S. Charles et al. https://doi.org/10.5194/hess-22-3533-2018
36. Evaluating Operational Risk in Environmental Modeling: Assessment of Reliability and Sharpness for Ensemble Selection S. Pokorny et al. https://doi.org/10.1061/JHYEFF.HEENG-5833
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39. Evaluating post-processing approaches for monthly and seasonal streamflow forecasts F. Woldemeskel et al. https://doi.org/10.5194/hess-22-6257-2018
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45. Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes Z. Huang & T. Zhao https://doi.org/10.1002/wat2.1580
46. Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations Y. Zhang et al. https://doi.org/10.5194/hess-27-4529-2023
47. Development of a national 7-day ensemble streamflow forecasting service for Australia H. Hapuarachchi et al. https://doi.org/10.5194/hess-26-4801-2022
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49. Study of teleconnection between hydrological variables and climatological variables in a headwater basin of the Maipo River for forecast model application J. Montalva et al. https://doi.org/10.24850/j-tyca-16-4-3
50. A simplified approach to produce probabilistic hydrological model predictions D. McInerney et al. https://doi.org/10.1016/j.envsoft.2018.07.001
51. Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. https://doi.org/10.3390/w16101438
52. A multi-model evaluation of probabilistic streamflow predictions via residual error modelling J. Romero-Cuellar et al. https://doi.org/10.1016/j.jhydrol.2024.131152
53. 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
54. Enhancing streamflow ensemble forecasting: evaluating pre- and post-processing strategies for a spatially distributed model A. Askarinejad et al. https://doi.org/10.1080/07011784.2025.2541629
55. Simulation of Gauged and Ungauged Streamflow of Coastal Catchments across Australia M. Bari et al. https://doi.org/10.3390/w16040527
56. Temporally varied error modelling for improving simulations and quantifying uncertainty L. Liu et al. https://doi.org/10.1016/j.jhydrol.2020.124914
57. Evaluation and Benchmarking of Operational Short-Range Ensemble Mean and Median Streamflow Forecasts for the Ohio River Basin T. Adams III & R. Dymond https://doi.org/10.1175/JHM-D-18-0102.1
58. Reliable hourly streamflow forecasting with emphasis on ephemeral rivers M. Li et al. https://doi.org/10.1016/j.jhydrol.2020.125739