29 citations as recorded by crossref.

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4. Regional Parameter Estimation of the SWAT Model: Methodology and Application to River Basins in the Peruvian Pacific Drainage F. Asurza-Véliz & W. Lavado-Casimiro 10.3390/w12113198
5. Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models G. Papacharalampous et al. 10.1016/j.advwatres.2019.103471
6. EvalHyd v0.1.2: a polyglot tool for the evaluation of deterministic and probabilistic streamflow predictions T. Hallouin et al. 10.5194/gmd-17-4561-2024
7. On the choice of calibration metrics for “high-flow” estimation using hydrologic models N. Mizukami et al. 10.5194/hess-23-2601-2019
8. Assessment of spatial transferability of process‐based hydrological model parameters in two neighbouring catchments in the Himalayan Region S. Nepal et al. 10.1002/hyp.11199
9. Quantifying uncertainty in simulated streamflow and runoff from a continental-scale monthly water balance model A. Bock et al. 10.1016/j.advwatres.2018.10.005
10. Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models H. Liu et al. 10.1002/hyp.14410
11. Random Forest Ability in Regionalizing Hourly Hydrological Model Parameters M. Saadi et al. 10.3390/w11081540
12. On the deterministic and stochastic use of hydrologic models W. Farmer & R. Vogel 10.1002/2016WR019129
13. A space-time geostatistical approach for ensemble rainfall nowcasting A. Caseri et al. 10.1051/e3sconf/20160718001
14. Evaluation of Uncertainty Intervals for Daily, Statistically Derived Streamflow Estimates at Ungaged Basins across the Continental U.S. S. Levin & W. Farmer 10.3390/w12051390
15. Evaluating Hydrological Models for Deriving Water Resources in Peninsular Spain J. Pérez-Sánchez et al. 10.3390/su11102872
16. Cumulative Effects of Uncertainty on Simulated Streamflow in a Hydrologic Modeling Environment S. Pokorny et al. 10.1525/elementa.431
17. Explanation and Probabilistic Prediction of Hydrological Signatures with Statistical Boosting Algorithms H. Tyralis et al. 10.3390/rs13030333
18. Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis E. Moges et al. 10.3390/w13010028
19. A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting G. Papacharalampous & H. Tyralis 10.3389/frwa.2022.961954
20. How to explain and predict the shape parameter of the generalized extreme value distribution of streamflow extremes using a big dataset H. Tyralis et al. 10.1016/j.jhydrol.2019.04.070
21. Estimation of uncertainty in flood forecasts—A comparison of methods L. Boelee et al. 10.1111/jfr3.12516
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23. A crash-testing framework for predictive uncertainty assessment when forecasting high flows in an extrapolation context L. Berthet et al. 10.5194/hess-24-2017-2020
24. Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms G. Papacharalampous et al. 10.3390/w11102126
25. A stochastic conceptual-data-driven approach for improved hydrological simulations J. Quilty et al. 10.1016/j.envsoft.2022.105326
26. Climate change impacts on the streamflow in Spanish basins monitored under near-natural conditions D. Pulido-Velazquez et al. 10.1016/j.ejrh.2021.100937
27. Vers une production en temps réel d'intervalles prédictifs associés aux prévisions de crue dans Vigicrues en France J. Viatgé et al. 10.1051/lhb/2019016
28. Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale G. Papacharalampous et al. 10.1016/j.advwatres.2019.103470
29. Large-sample hydrology: a need to balance depth with breadth H. Gupta et al. 10.5194/hess-18-463-2014