30 citations as recorded by crossref.

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2. High Resolution Water Table Modeling of the Shallow Groundwater Using a Knowledge-Guided Gradient Boosting Decision Tree Model J. Koch et al. 10.3389/frwa.2021.701726
3. A hybrid model for river water level forecasting: Cases of Xiangjiang River and Yuanjiang River, China Y. Li et al. 10.1016/j.jhydrol.2020.124934
4. Forecasting upper and lower uncertainty bands of river flood discharges with high predictive skill J. Leandro et al. 10.1016/j.jhydrol.2019.06.052
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6. The Potential of Knowing More: A Review of Data-Driven Urban Water Management S. Eggimann et al. 10.1021/acs.est.6b04267
7. Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas M. Rogelis & M. Werner 10.5194/hess-22-853-2018
8. Epistemic uncertainties and natural hazard risk assessment – Part 1: A review of different natural hazard areas K. Beven et al. 10.5194/nhess-18-2741-2018
9. 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
10. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. 10.1002/wat2.1246
11. Comparison of Different Configurations of Quantile Regression in Estimating Predictive Hydrological Uncertainty M. Muthusamy et al. 10.1016/j.proeng.2016.07.546
12. Quantile-Based Hydrological Modelling H. Tyralis & G. Papacharalampous 10.3390/w13233420
13. Skill of ensemble flood inundation forecasts at short- to medium-range timescales M. Gomez et al. 10.1016/j.jhydrol.2018.10.063
14. 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
15. Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O. Wani et al. 10.5194/hess-21-4021-2017
16. Comparison of different quantile regression methods to estimate predictive hydrological uncertainty in the Upper Chao Phraya River Basin, Thailand S. Acharya et al. 10.1111/jfr3.12585
17. Probabilistic Hydrological Post-Processing at Scale: Why and How to Apply Machine-Learning Quantile Regression Algorithms G. Papacharalampous et al. 10.3390/w11102126
18. Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods O. Rahmati et al. 10.1016/j.scitotenv.2019.06.320
19. Technical note: Combining quantile forecasts and predictive distributions of streamflows K. Bogner et al. 10.5194/hess-21-5493-2017
20. Diagnosing Credibility of a Large-Scale Conceptual Hydrological Model in Simulating Streamflow P. Paul et al. 10.1061/(ASCE)HE.1943-5584.0001766
21. Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system S. Sharma et al. 10.5194/hess-22-1831-2018
22. Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables F. Hoss & P. Fischbeck 10.5194/hess-19-3969-2015
23. Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments N. Dogulu et al. 10.5194/hess-19-3181-2015
24. Post-Processing of Stream Flows in Switzerland with an Emphasis on Low Flows and Floods K. Bogner et al. 10.3390/w8040115
25. Parametric uncertainty assessment of hydrological models: coupling UNEEC-P and a fuzzy general regression neural network A. Ahmadi et al. 10.1080/02626667.2019.1610565
26. 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
27. Local vs. integrated control of a variable refrigerant flow system using artificial neural networks K. Ahn et al. 10.1080/23744731.2020.1760636
28. Runoff Probability Prediction Model Based on Natural Gradient Boosting with Tree-Structured Parzen Estimator Optimization K. Shen et al. 10.3390/w14040545
29. Predictive Uncertainty Estimation of Hydrological Multi-Model Ensembles Using Pair-Copula Construction B. Klein et al. 10.3390/w8040125
30. Estimating predictive hydrological uncertainty by dressing deterministic and ensemble forecasts; a comparison, with application to Meuse and Rhine J. Verkade et al. 10.1016/j.jhydrol.2017.10.024