241 citations as recorded by crossref.

1. Kullback–Leibler Divergence as a Forecast Skill Score with Classic Reliability–Resolution–Uncertainty Decomposition S. Weijs et al. 10.1175/2010MWR3229.1
2. Observation uncertainty of satellite soil moisture products determined with physically-based modeling N. Wanders et al. 10.1016/j.rse.2012.09.004
3. Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors D. McInerney et al. 10.1002/2016WR019168
4. A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region W. Ren et al. 10.1016/j.gloplacha.2018.03.011
5. Temporally varied error modelling for improving simulations and quantifying uncertainty L. Liu et al. 10.1016/j.jhydrol.2020.124914
6. Tercile Forecasts for Extending the Horizon of Skillful Hydrological Predictions K. Bogner et al. 10.1175/JHM-D-21-0020.1
7. A Ranking of Hydrological Signatures Based on Their Predictability in Space N. Addor et al. 10.1029/2018WR022606
8. Improving Precipitation Forecasts by Generating Ensembles through Postprocessing D. Shrestha et al. 10.1175/MWR-D-14-00329.1
9. Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction B. Renard et al. 10.1029/2022JD037908
10. Implications of Ensemble Quantitative Precipitation Forecast Errors on Distributed Streamflow Forecasting G. Mascaro et al. 10.1175/2009JHM1144.1
11. Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment D. Kavetski et al. 10.1029/2010WR009525
12. Development of a national 7-day ensemble streamflow forecasting service for Australia H. Hapuarachchi et al. 10.5194/hess-26-4801-2022
13. Sensitivity of source sediment fingerprinting to tracer selection methods T. Chalaux-Clergue et al. 10.5194/soil-10-109-2024
14. Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times K. Engeland & I. Steinsland 10.1002/2012WR012757
15. Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. 10.3390/w16101438
16. Skilful seasonal forecasts of streamflow over Europe? L. Arnal et al. 10.5194/hess-22-2057-2018
17. How to evaluate sediment fingerprinting source apportionments P. Batista et al. 10.1007/s11368-022-03157-4
18. Validation of the Flood‐PROOFS probabilistic forecasting system P. Laiolo et al. 10.1002/hyp.9888
19. Development of statistical models for at‐site probabilistic seasonal rainfall forecast G. Villarini & F. Serinaldi 10.1002/joc.3393
20. A hybrid time- and signature-domain Bayesian inference framework for calibration of hydrological models: a case study in the Ren River basin in China S. Liu et al. 10.1007/s00477-022-02282-3
21. A parsimonious post-processor for uncertainty evaluation of ensemble precipitation forecasts: an application to quantitative precipitation forecasts for civil protection purposes D. Biondi et al. 10.2166/nh.2021.045
22. Propagation of uncertainty from observing systems and NWP into hydrological models: COST‐731 Working Group 2 M. Zappa et al. 10.1002/asl.248
23. Multi-step ahead probabilistic forecasting of multiple hydrological variables for multiple stations Z. Zhang et al. 10.1016/j.jhydrol.2023.129094
24. Validation of point process predictions with proper scoring rules C. Heinrich‐Mertsching et al. 10.1111/sjos.12736
25. Probabilistic Forecasting With Fuzzy Time Series P. de Lima Silva et al. 10.1109/TFUZZ.2019.2922152
26. Improving probabilistic streamflow predictions through a nonparametric residual error model J. Liang et al. 10.1016/j.envsoft.2024.105981
27. Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts R. Laugesen et al. 10.5194/hess-27-873-2023
28. Achieving high-quality probabilistic predictions from hydrological models calibrated with a wide range of objective functions J. Hunter et al. 10.1016/j.jhydrol.2021.126578
29. On the implementation of post-processing of runoff forecast ensembles J. Skøien et al. 10.1175/JHM-D-21-0008.1
30. Probabilistic Prediction of Separation Buffer to Compensate for the Closing Effect on Final Approach S. Förster et al. 10.3390/aerospace8020029
31. Real-time flood forecasting downstream river confluences using a Bayesian approach S. Barbetta et al. 10.1016/j.jhydrol.2018.08.043
32. Stochastic Watershed Model Ensembles for Long‐Range Planning: Verification and Validation G. Shabestanipour et al. 10.1029/2022WR032201
33. Hydrologic post-processing of MOPEX streamflow simulations A. Ye et al. 10.1016/j.jhydrol.2013.10.055
34. ImprovedBayesian multimodeling: Integration of copulas andBayesian model averaging S. Madadgar & H. Moradkhani 10.1002/2014WR015965
35. A hybrid approach to monthly streamflow forecasting: Integrating hydrological model outputs into a Bayesian artificial neural network G. Humphrey et al. 10.1016/j.jhydrol.2016.06.026
36. Quantification of the forecast uncertainty using conditional probability and updating models H. Ba et al. 10.2166/nh.2019.094
37. Early flood warnings from empirical (expanded) downscaling of the full ECMWF Ensemble Prediction System G. Bürger et al. 10.1029/2009WR007779
38. Improving the Reliability of Probabilistic Multi-Step-Ahead Flood Forecasting by Fusing Unscented Kalman Filter with Recurrent Neural Network Y. Zhou et al. 10.3390/w12020578
39. Quantifying predictive uncertainty of streamflow forecasts based on a Bayesian joint probability model T. Zhao et al. 10.1016/j.jhydrol.2015.06.043
40. Hybrid Models for Water Demand Forecasting P. Pandey et al. 10.1061/(ASCE)WR.1943-5452.0001331
41. On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark D. Lucatero et al. 10.5194/hess-22-6591-2018
42. On the assessment of reliability in probabilistic hydrometeorological event forecasting C. DeChant & H. Moradkhani 10.1002/2014WR016617
43. Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway K. Engeland et al. 10.1016/j.jhydrol.2016.02.036
44. Value of long‐term streamflow forecasts to reservoir operations for water supply in snow‐dominated river catchments D. Anghileri et al. 10.1002/2015WR017864
45. Why hydrological predictions should be evaluated using information theory S. Weijs et al. 10.5194/hess-14-2545-2010
46. 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
47. Belief elicitation with multiple point predictions M. Eyting & P. Schmidt 10.1016/j.euroecorev.2021.103700
48. Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment? B. Quesada‐Montano et al. 10.1002/hyp.11460
49. Improving real-time inflow forecasting into hydropower reservoirs through a complementary modelling framework A. Gragne et al. 10.5194/hess-19-3695-2015
50. Middle and Long-Term Runoff Probabilistic Forecasting Based on Gaussian Mixture Regression Y. Liu et al. 10.1007/s11269-019-02221-y
51. Case Study: A Real-Time Flood Forecasting System with Predictive Uncertainty Estimation for the Godavari River, India S. Barbetta et al. 10.3390/w8100463
52. Paradigmatic changes required in water resources management to benefit from probabilistic forecasts E. Todini 10.1016/j.wasec.2018.08.001
53. Uncertainty analysis of a spatially-distributed hydrological model with rainfall multipliers A. Datta & T. Bolisetti 10.1139/cjce-2015-0413
54. Exceedance probability estimation for a quality test consisting of multiple measurements S. Tamminen et al. 10.1016/j.eswa.2013.01.056
55. Water quality soft-sensor prediction in anaerobic process using deep neural network optimized by Tree-structured Parzen Estimator J. Li et al. 10.1007/s11783-023-1667-3
56. A Variable-Correlation Model to Characterize Asymmetric Dependence for Postprocessing Short-Term Precipitation Forecasts W. Li et al. 10.1175/MWR-D-19-0258.1
57. AR-GARCH with Exogenous Variables as a Postprocessing Model for Improving Streamflow Forecasts X. Zha et al. 10.1061/(ASCE)HE.1943-5584.0001955
58. Comparison of Precipitation and Streamflow Correcting for Ensemble Streamflow Forecasts Y. Li et al. 10.3390/w10020177
59. Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting T. Serafin et al. 10.3390/en12132561
60. Evaluating uncertainty estimates in hydrologic models: borrowing measures from the forecast verification community K. Franz & T. Hogue 10.5194/hess-15-3367-2011
61. A ‘Peak‐Box’ approach for supporting interpretation and verification of operational ensemble peak‐flow forecasts M. Zappa et al. 10.1002/hyp.9521
62. Evaluation of wind power forecasts—An up‐to‐date view J. Messner et al. 10.1002/we.2497
63. Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years M. Troin et al. 10.1029/2020WR028392
64. The Value of Subseasonal Hydrometeorological Forecasts to Hydropower Operations: How Much Does Preprocessing Matter? D. Anghileri et al. 10.1029/2019WR025280
65. Probabilistic Forecasting of Electricity Load with Inhomogeneous Markov Switching Models K. Berk 10.2139/ssrn.2954365
66. Comparative Study of GR4J and Xinanjiang Models in Humid Area 何. 王 10.12677/JWRR.2021.101002
67. Using Ensemble Streamflow Forecasts to Inform Seasonal Outlooks for Water Allocations in the Murray Darling Basin T. Graham et al. 10.1061/JWRMD5.WRENG-6099
68. Improving parameter priors for data-scarce estimation problems S. Almeida et al. 10.1002/wrcr.20437
69. Seasonal streamflow forecasting by conditioning climatology with precipitation indices L. Crochemore et al. 10.5194/hess-21-1573-2017
70. Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors B. Renard et al. 10.1029/2009WR008328
71. Statistical downscaling of precipitation on a spatially dependent network using a regional climate model R. Erhardt et al. 10.1007/s00477-014-0988-y
72. Multi-model ensemble forecasting of North Atlantic tropical cyclone activity G. Villarini et al. 10.1007/s00382-016-3369-z
73. A practical approach to the assessment of probabilistic flow predictions S. Liguori & M. Rico‐Ramirez 10.1002/hyp.9468
74. A data-based comparison of flood frequency analysis methods used in France K. Kochanek et al. 10.5194/nhess-14-295-2014
75. An Evaluation of Model Output Statistics for Subseasonal Streamflow Forecasting in European Catchments S. Schick et al. 10.1175/JHM-D-18-0195.1
76. Of Quantiles and Expectiles: Consistent Scoring Functions, Choquet Representations and Forecast Rankings W. Ehm et al. 10.1111/rssb.12154
77. Short-Term Density Forecasting of Low-Voltage Load Using Bernstein-Polynomial Normalizing Flows M. Arpogaus et al. 10.1109/TSG.2023.3254890
78. Evaluation of the ECMWF System 4 climate forecasts for streamflow forecasting in the Upper Hanjiang River Basin F. Tian et al. 10.2166/nh.2018.176
79. Characterising performance of environmental models N. Bennett et al. 10.1016/j.envsoft.2012.09.011
80. Comparing Density Forecasts Using Threshold- and Quantile-Weighted Scoring Rules T. Gneiting & R. Ranjan 10.1198/jbes.2010.08110
81. Validation of hydrological models: Conceptual basis, methodological approaches and a proposal for a code of practice D. Biondi et al. 10.1016/j.pce.2011.07.037
82. Probabilistic Flood Forecasting Using Hydrologic Uncertainty Processor with Ensemble Weather Forecasts S. Han & P. Coulibaly 10.1175/JHM-D-18-0251.1
83. Confidence intervals for the coefficient of L-variation in hydrological applications A. Viglione 10.5194/hess-14-2229-2010
84. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios N. Addor et al. 10.5194/hess-15-2327-2011
85. 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
86. Assessing parameter, precipitation, and predictive uncertainty in a distributed hydrological model using sequential data assimilation with the particle filter P. Salamon & L. Feyen 10.1016/j.jhydrol.2009.07.051
87. Error reduction and representation in stages (ERRIS) in hydrological modelling for ensemble streamflow forecasting M. Li et al. 10.5194/hess-20-3561-2016
88. A Value‐Based Model Selection Approach for Environmental Random Variables M. Müller & S. Thompson 10.1029/2018WR023000
89. Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting O. Wani et al. 10.5194/hess-21-4021-2017
90. Downscaled numerical weather predictions can improve forecasts of sugarcane irrigation indices A. Schepen et al. 10.1016/j.compag.2024.109009
91. Application of variance decomposition approach in the uncertainty analysis of a hydrological model A. Datta & T. Bolisetti 10.1139/cjce-2012-0337
92. Statistical processing of forecasts for hydrological ensemble prediction: a comparative study of different bias correction strategies I. Zalachori et al. 10.5194/asr-8-135-2012
93. Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting F. Bourgin et al. 10.1016/j.jhydrol.2014.07.054
94. An ensemble deep learning approach to spatiotemporal tropospheric ozone forecasting: A case study of Tehran, Iran M. Rezaali et al. 10.1016/j.uclim.2024.101950
95. Learning to Forecast: The Probabilistic Time Series Forecasting Challenge J. Bracher et al. 10.1080/00031305.2023.2199800
96. Real-time simulation of surface water and groundwater with data assimilation X. He et al. 10.1016/j.advwatres.2019.03.004
97. Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation R. Sun et al. 10.1016/j.jhydrol.2017.09.041
98. Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times S. Donegan et al. 10.5194/hess-25-4159-2021
99. Hydrological uncertainty processor based on a copula function Z. Liu et al. 10.1080/02626667.2017.1410278
100. Multiseason Lead Forecast of the North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE) G. Villarini & G. Vecchi 10.1175/JCLI-D-12-00448.1
101. Study of early flood warning based on postprocessed predicted precipitation and Xinanjiang model X. Jiang et al. 10.1016/j.wace.2023.100611
102. Integrating different types of information into hydrological model parameter estimation: Application to ungauged catchments and land use scenario analysis N. Bulygina et al. 10.1029/2011WR011207
103. Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes P. Hublart et al. 10.5194/hess-20-3691-2016
104. A step toward global-scale applicability and transferability of flow duration curve studies: A flow duration curve review (2000–2020) C. Leong & Y. Yokoo 10.1016/j.jhydrol.2021.126984
105. Multisite probabilistic forecasting of seasonal flows for streams with zero value occurrences Q. Wang & D. Robertson 10.1029/2010WR009333
106. Comparing Hydrological Postprocessors Including Ensemble Predictions Into Full Predictive Probability Distribution of Streamflow D. Biondi & E. Todini 10.1029/2017WR022432
107. Revealing Hidden Climate Indices from the Occurrence of Hydrologic Extremes B. Renard & M. Thyer 10.1029/2019WR024951
108. Decomposition and graphical portrayal of the quantile score S. Bentzien & P. Friederichs 10.1002/qj.2284
109. Improving the evaluation of hydrological multi-model forecast performance in the Upper Danube Catchment K. Bogner et al. 10.1080/15715124.2011.625359
110. Development of PCA-based cluster quantile regression (PCA-CQR) framework for streamflow prediction: Application to the Xiangxi river watershed, China Y. Fan et al. 10.1016/j.asoc.2016.11.039
111. Deep Learning for Time Series Forecasting: Tutorial and Literature Survey K. Benidis et al. 10.1145/3533382
112. Uncertainty estimation with deep learning for rainfall–runoff modeling D. Klotz et al. 10.5194/hess-26-1673-2022
113. 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
114. Delayed response to environmental conditions and infra-seasonal dynamics of the short-beaked common dolphin distribution C. Lambert et al. 10.1098/rsos.220379
115. Disentangling timing and amplitude errors in streamflow simulations S. Seibert et al. 10.5194/hess-20-3745-2016
116. A short-term probabilistic photovoltaic power prediction method based on feature selection and improved LSTM neural network R. Liu et al. 10.1016/j.epsr.2022.108069
117. Uncertainty in Flow Time-Series Predictions in a Tropical Monsoon-Dominated Catchment in Northern Thailand S. Visessri & N. McIntyre 10.1061/(ASCE)HE.1943-5584.0001407
118. An intercomparison of approaches for improving operational seasonal streamflow forecasts P. Mendoza et al. 10.5194/hess-21-3915-2017
119. Integration and Evaluation of Forecast-Informed Multiobjective Reservoir Operations G. Yang et al. 10.1061/(ASCE)WR.1943-5452.0001229
120. Assessing Entropy-based Bayesian Model Averaging Method for Probabilistic Precipitation Forecasting 10.1175/JHM-D-21-0086.1
121. Web-Based Environmental Simulation: Bridging the Gap between Scientific Modeling and Decision-Making W. Buytaert et al. 10.1021/es2031278
122. Deriving reservoir operation rule based on Bayesian deep learning method considering multiple uncertainties Y. Liu et al. 10.1016/j.jhydrol.2019.124207
123. Event and model dependent rainfall adjustments to improve discharge predictions D. Fuentes-Andino et al. 10.1080/02626667.2016.1183775
124. Predictive uncertainty assessment in flood forecasting using quantile regression A. M. K. & C. N. R 10.2166/h2oj.2023.040
125. An Analysis of the Soil Moisture Feedback on Convective and Stratiform Precipitation L. Alfieri et al. 10.1175/2007JHM863.1
126. Evaluation of a probabilistic hydrometeorological forecast system S. Jaun & B. Ahrens 10.5194/hess-13-1031-2009
127. Wind speed forecasting based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation Z. Zhang et al. 10.1016/j.enconman.2019.06.024
128. Bayesian Neural Networks for Uncertainty Analysis of Hydrologic Modeling: A Comparison of Two Schemes X. Zhang & K. Zhao 10.1007/s11269-012-0021-5
129. Conditional Density Forecast of Electricity Price Based on Ensemble ELM and Logistic EMOS S. Chai et al. 10.1109/TSG.2018.2817284
130. Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods S. Charles et al. 10.5194/hess-22-3533-2018
131. Impact of the quality of hydrological forecasts on the management and revenue of hydroelectric reservoirs – a conceptual approach M. Cassagnole et al. 10.5194/hess-25-1033-2021
132. Changes in the distribution of annual maximum temperatures in Europe G. Auld et al. 10.5194/ascmo-9-45-2023
133. Multi-scale hydrometeorological observation and modelling for flash flood understanding I. Braud et al. 10.5194/hess-18-3733-2014
134. Verification of High-Resolution Medium-Range Precipitation Forecasts from Global Environmental Multiscale Model over China during 2009–2013 H. Xu et al. 10.3390/atmos9030104
135. Data‐based comparison of frequency analysis methods: A general framework B. Renard et al. 10.1002/wrcr.20087
136. Estimating the Uncertainty of Hydrological Predictions through Data-Driven Resampling Techniques A. Sikorska et al. 10.1061/(ASCE)HE.1943-5584.0000926
137. A blueprint for process‐based modeling of uncertain hydrological systems A. Montanari & D. Koutsoyiannis 10.1029/2011WR011412
138. How to assess climate change impact models: uncertainty analysis of streamflow statistics via approximate Bayesian computation (ABC) J. Romero-Cuellar & F. Francés 10.1080/02626667.2023.2231437
139. Estimating the uncertainty of hydrological forecasts: A statistical approach A. Montanari & G. Grossi 10.1029/2008WR006897
140. Technical note: Combining quantile forecasts and predictive distributions of streamflows K. Bogner et al. 10.5194/hess-21-5493-2017
141. Evaluating Forecasts for High-Impact Events Using Transformed Kernel Scores S. Allen et al. 10.1137/22M1532184
142. A Bayesian hierarchical approach to regional frequency analysis B. Renard 10.1029/2010WR010089
143. The reduction continuous rank probability score for evaluating discharge forecasts from hydrological ensemble prediction systems B. Trinh et al. 10.1002/asl2.417
144. A Seasonally Coherent Calibration (SCC) Model for Postprocessing Numerical Weather Predictions Q. Wang et al. 10.1175/MWR-D-19-0108.1
145. Predictive Uncertainty Estimation in Water Demand Forecasting Using the Model Conditional Processor A. Anele et al. 10.3390/w10040475
146. Ensemble hydro-meteorological simulation for flash flood early detection in southern Switzerland L. Alfieri et al. 10.1016/j.jhydrol.2011.12.038
147. Superposition of three sources of uncertainties in operational flood forecasting chains M. Zappa et al. 10.1016/j.atmosres.2010.12.005
148. On noise specification in data assimilation schemes for improved flood forecasting using distributed hydrological models S. Noh et al. 10.1016/j.jhydrol.2014.07.049
149. A copula-based time series model for global horizontal irradiation A. Müller & M. Reuber 10.1016/j.ijforecast.2022.02.011
150. Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting X. Zhang et al. 10.1016/j.jhydrol.2011.09.002
151. A Hidden Climate Indices Modeling Framework for Multivariable Space‐Time Data B. Renard et al. 10.1029/2021WR030007
152. A review of efficiency criteria suitable for evaluating low-flow simulations R. Pushpalatha et al. 10.1016/j.jhydrol.2011.11.055
153. Uncertainty-based multi-criteria calibration of rainfall-runoff models: a comparative study M. Shafii et al. 10.1007/s00477-014-0855-x
154. A stochastic conceptual-data-driven approach for improved hydrological simulations J. Quilty et al. 10.1016/j.envsoft.2022.105326
155. The GRAPES evaluation tools based on Python (GetPy) B. Zhao et al. 10.1007/s42514-022-00127-7
156. Estimating uncertainty of streamflow simulation using Bayesian neural networks X. Zhang et al. 10.1029/2008WR007030
157. Improvement of rank histograms for verifying the reliability of extreme event ensemble forecasts J. Xu et al. 10.1016/j.envsoft.2017.02.024
158. Assessing Hydrologic Uncertainty Processor Performance for Flood Forecasting in a Semiurban Watershed S. Han et al. 10.1061/(ASCE)HE.1943-5584.0001828
159. Gaussian mixture model coupled recurrent neural networks for wind speed interval forecast S. Zhu et al. 10.1016/j.enconman.2019.06.083
160. Deterministic and probabilistic evaluation of raw and post-processing monthly precipitation forecasts: a case study of China Y. Li et al. 10.2166/hydro.2021.176
161. Evaluation of statistical models for forecast errors from the HBV model K. Engeland et al. 10.1016/j.jhydrol.2010.01.018
162. A weighted ensemble of regional climate projections for exploring the spatiotemporal evolution of multidimensional drought risks in a changing climate B. Zhang et al. 10.1007/s00382-021-05889-4
163. Toward a statistical framework to quantify the uncertainties of hydrologic response under climate change S. Steinschneider et al. 10.1029/2011WR011318
164. Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios A. Gelfan et al. 10.5194/hess-22-2073-2018
165. Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis M. Thyer et al. 10.1029/2008WR006825
166. Fluvial Flood Losses in the Contiguous United States Under Climate Change M. Rashid et al. 10.1029/2022EF003328
167. Error Prediction of Air Quality at Monitoring Stations Using Random Forest in a Total Error Framework J. Lepioufle et al. 10.3390/s21062160
168. Probabilistic estimates of drought impacts on agricultural production S. Madadgar et al. 10.1002/2017GL073606
169. New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics V. Resseguier et al. 10.1007/s11831-020-09437-x
170. Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts L. Crochemore et al. 10.5194/hess-20-3601-2016
171. Evaluating epidemic forecasts in an interval format J. Bracher et al. 10.1371/journal.pcbi.1008618
172. Post-Processing of Stream Flows in Switzerland with an Emphasis on Low Flows and Floods K. Bogner et al. 10.3390/w8040115
173. Statistical Postprocessing of High-Resolution Regional Climate Model Output P. Mendoza et al. 10.1175/MWR-D-14-00159.1
174. HESS Opinions "On forecast (in)consistency in a hydro-meteorological chain: curse or blessing?" F. Pappenberger et al. 10.5194/hess-15-2391-2011
175. Seasonal streamflow forecasting by surrogate modeling in the Yarlung Zangbo River Basin, China H. Gu et al. 10.1016/j.ejrh.2024.101835
176. Evaluating the discrimination ability of proper multi-variate scoring rules C. Alexander et al. 10.1007/s10479-022-04611-9
177. Operation rule extraction based on deep learning model with attention mechanism for wind-solar-hydro hybrid system under multiple uncertainties Z. Zhang et al. 10.1016/j.renene.2021.01.115
178. Stochastic description of infiltration between aquifers S. Tamea & I. Butera 10.1016/j.jhydrol.2013.12.007
179. Hydrologic multi-model ensemble predictions using variational Bayesian deep learning D. Li et al. 10.1016/j.jhydrol.2021.127221
180. Toward a reliable prediction of seasonal forecast uncertainty: Addressing model and initial condition uncertainty with ensemble data assimilation and Sequential Bayesian Combination C. DeChant & H. Moradkhani 10.1016/j.jhydrol.2014.05.045
181. Impact of Stage Measurement Errors on Streamflow Uncertainty I. Horner et al. 10.1002/2017WR022039
182. A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites Q. Wang et al. 10.1029/2008WR007355
183. Towards an Extension of the Model Conditional Processor: Predictive Uncertainty Quantification of Monthly Streamflow via Gaussian Mixture Models and Clusters J. Romero-Cuellar et al. 10.3390/w14081261
184. Improving streamflow estimation in ungauged basins using a multi-modelling approach T. Razavi & P. Coulibaly 10.1080/02626667.2016.1154558
185. Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation B. Renard et al. 10.1029/2011WR010643
186. Robust estimation of a location parameter with the integrated Hogg function L. Catania & A. Luati 10.1016/j.spl.2020.108812
187. Multiscale error analysis, correction, and predictive uncertainty estimation in a flood forecasting system K. Bogner & F. Pappenberger 10.1029/2010WR009137
188. Predictive performance of ensemble hydroclimatic forecasts: Verification metrics, diagnostic plots and forecast attributes Z. Huang & T. Zhao 10.1002/wat2.1580
189. Combination of Multiple Data-Driven Models for Long-Term Monthly Runoff Predictions Based on Bayesian Model Averaging H. Huang et al. 10.1007/s11269-019-02305-9
190. Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. 10.5194/hess-27-4385-2023
191. Probabilistic assessment of crop yield loss to drought time‐scales in Xinjiang, China H. Li et al. 10.1002/joc.7059
192. Variational Bayesian Neural Network for Ensemble Flood Forecasting X. Zhan et al. 10.3390/w12102740
193. Toward Improved Probabilistic Predictions for Flood Forecasts Generated Using Deterministic Models X. Jiang et al. 10.1029/2019WR025477
194. 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
195. Coupling forecast calibration and data‐driven downscaling for generating reliable, high‐resolution, multivariate seasonal climate forecast ensembles at multiple sites A. Schepen et al. 10.1002/joc.6346
196. A System for Continuous Hydrological Ensemble Forecasting (SCHEF) to lead times of 9 days J. Bennett et al. 10.1016/j.jhydrol.2014.08.010
197. Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation C. DeChant & H. Moradkhani 10.5194/hess-15-3399-2011
198. Impact of EMD decomposition and random initialisation of weights in ANN hindcasting of daily stream flow series: An empirical examination G. Napolitano et al. 10.1016/j.jhydrol.2011.06.015
199. Flood frequency hydrology: 3. A Bayesian analysis A. Viglione et al. 10.1029/2011WR010782
200. Hydrological post-processing based on approximate Bayesian computation (ABC) J. Romero-Cuellar et al. 10.1007/s00477-019-01694-y
201. Technical Note: The normal quantile transformation and its application in a flood forecasting system K. Bogner et al. 10.5194/hess-16-1085-2012
202. Flood Routing Model with Particle Filter-Based Data Assimilation for Flash Flood Forecasting in the Micro-Model of Lower Yellow River, China M. Chen et al. 10.3390/w10111612
203. Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression Y. Liu et al. 10.1016/j.jhydrol.2018.03.057
204. Flood forecasting for heteroscedastic streamflow processes F. Pianosi & L. Raso 10.3182/20080706-5-KR-1001.02462
205. Scores for Multivariate Distributions and Level Sets X. Meng et al. 10.1287/opre.2020.0365
206. Benchmark probabilistic solar forecasts: Characteristics and recommendations K. Doubleday et al. 10.1016/j.solener.2020.05.051
207. Ensemble flood forecasting: A review H. Cloke & F. Pappenberger 10.1016/j.jhydrol.2009.06.005
208. A hierarchicalBayesian regional model for nonstationary precipitation extremes inNorthernCalifornia conditioned on tropical moisture exports S. Steinschneider & U. Lall 10.1002/2014WR016664
209. Snow hydrology signatures for model identification within a limits‐of‐acceptability approach B. Schaefli 10.1002/hyp.10972
210. Nonlinear response of runoff to atmospheric freezing level height variation based on hybrid prediction models Y. Qin et al. 10.1080/02626667.2019.1662023
211. 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
212. A regional Bayesian hierarchical model for flood frequency analysis H. Yan & H. Moradkhani 10.1007/s00477-014-0975-3
213. Factors Influencing the Performance of Regression-Based Statistical Postprocessing Models for Short-Term Precipitation Forecasts W. Li et al. 10.1175/WAF-D-19-0121.1
214. Bayesian structured additive distributional regression with an application to regional income inequality in Germany N. Klein et al. 10.1214/15-AOAS823
215. 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
216. Bluecat: A Local Uncertainty Estimator for Deterministic Simulations and Predictions D. Koutsoyiannis & A. Montanari 10.1029/2021WR031215
217. Bayesian Conditional Transformation Models M. Carlan et al. 10.1080/01621459.2023.2191820
218. Exceedance Probability Score: A Novel Measure for Comparing Probabilistic Predictions I. Juutilainen et al. 10.1080/15598608.2012.695663
219. Using multiple satellite-gauge merged precipitation products ensemble for hydrologic uncertainty analysis over the Huaihe River basin R. Sun et al. 10.1016/j.jhydrol.2018.09.024
220. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments S. Almeida et al. 10.5194/hess-20-887-2016
221. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene S. Thompson et al. 10.5194/hess-17-5013-2013
222. Probabilistic Learning of Multivariate Time Series with Temporal Irregularity Y. LI et al. 10.2139/ssrn.4482654
223. Regularized quantile regression averaging for probabilistic electricity price forecasting B. Uniejewski & R. Weron 10.1016/j.eneco.2021.105121
224. Hypothesis testing for performance evaluation of probabilistic seasonal rainfall forecasts K. Cheng et al. 10.1186/s40562-024-00341-x
225. A real-time probabilistic channel flood-forecasting model based on the Bayesian particle filter approach X. Xu et al. 10.1016/j.envsoft.2016.11.010
226. Robust streamflow forecasting: a Student’s t-mixture vector autoregressive model M. Favereau et al. 10.1007/s00477-022-02241-y
227. Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. 10.5194/hess-22-3601-2018
228. Hydrological post-processing of streamflow forecasts issued from multimodel ensemble prediction systems J. Xu et al. 10.1016/j.jhydrol.2019.124002
229. Evaluating post-processing approaches for monthly and seasonal streamflow forecasts F. Woldemeskel et al. 10.5194/hess-22-6257-2018
230. Flood Forecasting and Decision Making in the new Millennium. Where are We? E. Todini 10.1007/s11269-017-1693-7
231. Use of a national flood mark database to estimate flood hazard in the distant past B. Renard 10.1080/02626667.2023.2212165
232. Forecast verification for extreme value distributions with an application to probabilistic peak wind prediction P. Friederichs & T. Thorarinsdottir 10.1002/env.2176
233. Introducing entropy-based Bayesian model averaging for streamflow forecast P. Darbandsari & P. Coulibaly 10.1016/j.jhydrol.2020.125577
234. Probabilistic forecasting of industrial electricity load with regime switching behavior K. Berk et al. 10.1016/j.ijforecast.2017.09.006
235. Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model S. Mustafa et al. 10.1029/2017WR021857
236. Probabilistic Day-Ahead Inertia Forecasting E. Heylen et al. 10.1109/TPWRS.2021.3134811
237. Rainfall events prediction using rule-based fuzzy inference system S. Asklany et al. 10.1016/j.atmosres.2011.02.015
238. Post-processing of reservoir releases to support real-time reservoir operation and its effects on downstream hydrological alterations S. He et al. 10.1016/j.jhydrol.2021.126073
239. Model Complexity and Out-of-Sample Performance: Evidence from S&P 500 Index Returns A. Kaeck et al. 10.1016/j.jedc.2018.01.040
240. Probabilistic prediction of real‐world time series: A local regression approach F. Laio et al. 10.1029/2006GL028776
241. Evaluation of a global ensemble flood prediction system in Peru K. Bischiniotis et al. 10.1080/02626667.2019.1617868