88 citations as recorded by crossref.

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31. A generalised Dynamic Overflow Risk Assessment (DORA) for Real Time Control of urban drainage systems L. Vezzaro & M. Grum 10.1016/j.jhydrol.2014.05.019
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33. Assessment of predictive uncertainty within the framework of water demand forecasting using the Model Conditional Processor (MCP) S. Alvisi & M. Franchini 10.1080/1573062X.2015.1057182
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49. Performance assessment of a Bayesian Forecasting System (BFS) for real-time flood forecasting D. Biondi & D. De Luca 10.1016/j.jhydrol.2012.11.019
50. 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
51. Quantification of the forecast uncertainty using conditional probability and updating models H. Ba et al. 10.2166/nh.2019.094
52. Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O. Wani et al. 10.5194/hess-21-4021-2017
53. 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
54. Characterizing the uncertainty in river stage forecasts conditional on point forecast values J. Yan et al. 10.1029/2012WR011818
55. Performance evaluation of enterprises’ innovation capacity based on fuzzy system model and convolutional neural network A. Abudureheman et al. 10.3233/JIFS-179929
56. Overview, Comparative Assessment and Recommendations of Forecasting Models for Short-Term Water Demand Prediction A. Anele et al. 10.3390/w9110887
57. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. 10.1002/wat2.1246
58. Quantifying predictive uncertainty of streamflow forecasts based on a Bayesian joint probability model T. Zhao et al. 10.1016/j.jhydrol.2015.06.043
59. 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
60. Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics T. Baracchini et al. 10.1016/j.watres.2020.115529
61. Creating consistent datasets by combining remotely-sensed data and land surface model estimates through Bayesian uncertainty post-processing: The case of Land Surface Temperature from HIRS G. Coccia et al. 10.1016/j.rse.2015.09.010
62. Building a Multimodel Flood Prediction System with the TIGGE Archive E. Zsótér et al. 10.1175/JHM-D-15-0130.1
63. Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting F. Bourgin et al. 10.1016/j.jhydrol.2014.07.054
64. 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
65. Predictive Uncertainty Estimation on a Precipitation and Temperature Reanalysis Ensemble for Shigar Basin, Central Karakoram P. Reggiani et al. 10.3390/w8060263
66. 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
67. Validation of the AROME, ALADIN and WRF Meteorological Models for Flood Forecasting in Morocco E. El Khalki et al. 10.3390/w12020437
68. Does increased hydrochemical model complexity decrease robustness? C. Medici et al. 10.1016/j.jhydrol.2012.02.047
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70. A Bayesian Processor of Uncertainty for Precipitation Forecasting Using Multiple Predictors and Censoring P. Reggiani & O. Boyko 10.1175/MWR-D-19-0066.1
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72. Flood Forecasting and Decision Making in the new Millennium. Where are We? E. Todini 10.1007/s11269-017-1693-7
73. Addressing effective real-time forecasting inflows to dams through predictive uncertainty estimate S. Barbetta et al. 10.1016/j.jhydrol.2023.129512
74. Compound flood models in coastal areas: a review of methods and uncertainty analysis K. Xu et al. 10.1007/s11069-022-05683-3
75. 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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81. 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
82. Statistical Post-Processing to Improve Hydrometeorological Forecasts 青. 段 10.12677/JWRR.2012.14023
83. Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling L. Li et al. 10.1016/j.jhydrol.2013.02.002
84. 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
85. Post‐processing hydrological ensemble predictions intercomparison experiment S. van Andel et al. 10.1002/hyp.9595
86. Real-Time Dynamic Hydraulic Model of Water Distribution Networks A. Abu-Mahfouz et al. 10.3390/w11030470
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