13 citations as recorded by crossref.

1. Hydrological post-processing using stacked generalization of quantile regression algorithms: Large-scale application over CONUS H. Tyralis et al. 10.1016/j.jhydrol.2019.123957
2. Adjusting for Conditional Bias in Process Model Simulations of Hydrological Extremes: An Experiment Using the North Wyke Farm Platform S. Curceac et al. 10.3389/frai.2020.565859
3. Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
4. A Finite Mixture Modelling Perspective for Combining Experts’ Opinions with an Application to Quantile-Based Risk Measures D. Makariou et al. 10.3390/risks9060115
5. Quantile-Based Hydrological Modelling H. Tyralis & G. Papacharalampous 10.3390/w13233420
6. Machine Learning Techniques for Predicting the Energy Consumption/Production and Its Uncertainties Driven by Meteorological Observations and Forecasts K. Bogner et al. 10.3390/su11123328
7. Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms G. Papacharalampous et al. 10.3390/w11102126
8. Temporally varied error modelling for improving simulations and quantifying uncertainty L. Liu et al. 10.1016/j.jhydrol.2020.124914
9. Sequential aggregation of probabilistic forecasts—Application to wind speed ensemble forecasts M. Zamo et al. 10.1111/rssc.12455
10. The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter? D. Anghileri et al. 10.1029/2019WR025280
11. Online Aggregation of Probabilistic Forecasts Based on the Continuous Ranked Probability Score V. V’yugin & V. Trunov 10.1134/S1064226920060285
12. Seasonal Drought Prediction: Advances, Challenges, and Future Prospects Z. Hao et al. 10.1002/2016RG000549
13. A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed L. Slater et al. 10.1007/s00382-017-3794-7