88 citations as recorded by crossref.

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50. Predictive Uncertainty Estimation in Water Demand Forecasting Using the Model Conditional Processor A. Anele et al. 10.3390/w10040475
51. Patterns of runoff and sediment production in response to land-use changes in an ungauged Mediterranean catchment X. Rodriguez-Lloveras et al. 10.1016/j.jhydrol.2015.11.014
52. Quantification of the forecast uncertainty using conditional probability and updating models H. Ba et al. 10.2166/nh.2019.094
53. Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O. Wani et al. 10.5194/hess-21-4021-2017
54. Complementing near-real time satellite rainfall products with satellite soil moisture-derived rainfall through a Bayesian Inversion approach C. Massari et al. 10.1016/j.jhydrol.2019.03.038
55. Characterizing the uncertainty in river stage forecasts conditional on point forecast values J. Yan et al. 10.1029/2012WR011818
56. Performance evaluation of enterprises’ innovation capacity based on fuzzy system model and convolutional neural network A. Abudureheman et al. 10.3233/JIFS-179929
57. Overview, Comparative Assessment and Recommendations of Forecasting Models for Short-Term Water Demand Prediction A. Anele et al. 10.3390/w9110887
58. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. 10.1002/wat2.1246
59. Quantifying predictive uncertainty of streamflow forecasts based on a Bayesian joint probability model T. Zhao et al. 10.1016/j.jhydrol.2015.06.043
60. Consideration of streamflow forecast uncertainty in the development of short-term hydropower station optimal operation schemes: A novel approach based on mean-variance theory Y. Liu et al. 10.1016/j.jclepro.2021.126929
61. Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics T. Baracchini et al. 10.1016/j.watres.2020.115529
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63. Building a Multimodel Flood Prediction System with the TIGGE Archive E. Zsótér et al. 10.1175/JHM-D-15-0130.1
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65. A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction M. Ghorbani et al. 10.1007/s12665-015-5096-x
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67. Explore a Multivariate Bayesian Uncertainty Processor driven by artificial neural networks for probabilistic PM2.5 forecasting Y. Zhou et al. 10.1016/j.scitotenv.2019.134792
68. Validation of the AROME, ALADIN and WRF Meteorological Models for Flood Forecasting in Morocco E. El Khalki et al. 10.3390/w12020437
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75. Compound flood models in coastal areas: a review of methods and uncertainty analysis K. Xu et al. 10.1007/s11069-022-05683-3
76. The Science of NOAA's Operational Hydrologic Ensemble Forecast Service J. Demargne et al. 10.1175/BAMS-D-12-00081.1
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82. Enhancing real-time streamflow forecasts with wavelet-neural network based error-updating schemes and ECMWF meteorological predictions in Variable Infiltration Capacity model T. Nanda et al. 10.1016/j.jhydrol.2019.05.051
83. Statistical Post-Processing to Improve Hydrometeorological Forecasts 青. 段 10.12677/JWRR.2012.14023
84. Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling L. Li et al. 10.1016/j.jhydrol.2013.02.002
85. A non-parametric data-based approach for probabilistic flood forecasting in support of uncertainty communication N. Van Steenbergen et al. 10.1016/j.envsoft.2012.01.013
86. Post‐processing hydrological ensemble predictions intercomparison experiment S. van Andel et al. 10.1002/hyp.9595
87. Uncertainty estimates by Bayesian method with likelihood of AR (1) plus Normal model and AR (1) plus Multi-Normal model in different time-scales hydrological models L. Li et al. 10.1016/j.jhydrol.2011.05.052
88. Model uncertainty analysis by variance decomposition P. Willems 10.1016/j.pce.2011.07.003