112 citations as recorded by crossref.

1. Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas M. Rogelis & M. Werner 10.5194/hess-22-853-2018
2. Statistical refinement of the North American Multi-Model Ensemble precipitation forecasts over Karoon basin, Iran F. Yazdandoost et al. 10.2166/wcc.2023.277
3. 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
4. Generating Calibrated Ensembles of Physically Realistic, High-Resolution Precipitation Forecast Fields Based on GEFS Model Output M. Scheuerer & T. Hamill 10.1175/JHM-D-18-0067.1
5. A Smart Post-Processing System for Forecasting the Climate Precipitation Based on Machine Learning Computations A. Ghazikhani et al. 10.3390/su14116624
6. Reliability of Ensemble Climatological Forecasts Z. Huang et al. 10.1029/2023WR034942
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8. Convolutional neural network-based statistical post-processing of ensemble precipitation forecasts W. Li et al. 10.1016/j.jhydrol.2021.127301
9. Quantifying predictive uncertainty of streamflow forecasts based on a Bayesian joint probability model T. Zhao et al. 10.1016/j.jhydrol.2015.06.043
10. A Similarity-Based Implementation of the Schaake Shuffle R. Schefzik 10.1175/MWR-D-15-0227.1
11. Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes C. Alvarez-Garreton et al. 10.5194/hess-19-1659-2015
12. Monthly streamflow forecasting by machine learning methods using dynamic weather prediction model outputs over Iran M. Akbarian et al. 10.1016/j.jhydrol.2023.129480
13. Insights to key operational questions in forecast-informed dam release operation: case of Hume Dam T. Ng & D. Robertson 10.1080/13241583.2024.2392312
14. Impacts of Hydrometeor Drift on Orographic Precipitation: Two Case Studies of Landfalling Atmospheric Rivers in British Columbia, Canada R. Mo et al. 10.1175/WAF-D-18-0176.1
15. A two-stage blending approach for merging multiple satellite precipitation estimates and rain gauge observations: an experiment in the northeastern Tibetan Plateau Y. Ma et al. 10.5194/hess-25-359-2021
16. Assessing Entropy-based Bayesian Model Averaging Method for Probabilistic Precipitation Forecasting 10.1175/JHM-D-21-0086.1
17. Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871 L. Caillouet et al. 10.5194/hess-21-2923-2017
18. Application of weather post-processing methods for operational ensemble hydrological forecasting on multiple catchments in Canada F. Aguilar Andrade et al. 10.1016/j.jhydrol.2024.131861
19. A five-parameter Gamma-Gaussian model to calibrate monthly and seasonal GCM precipitation forecasts Z. Huang et al. 10.1016/j.jhydrol.2021.126893
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21. Efficient River Management using Stochastic MPC and Ensemble Forecast of Uncertain In-flows ⁎ ⁎The first and the third authors acknowledge the financial support from the Australian Research Council Linkage Project (LP130100605) and the Brescia Smart Living Project (MIURSCN00416) respectively. H. Nasir et al. 10.1016/j.ifacol.2018.06.196
22. Error reduction and representation in stages (ERRIS) in hydrological modelling for ensemble streamflow forecasting M. Li et al. 10.5194/hess-20-3561-2016
23. An evaluation of a methodology for seasonal soil water forecasting for Australian dry land cropping systems A. Western et al. 10.1016/j.agrformet.2018.02.012
24. An evaluation of post-processed TIGGE multimodel ensemble precipitation forecast in the Huai river basin Y. Tao et al. 10.1016/j.jhydrol.2014.04.040
25. Post-processing quantitative precipitation forecasts using the seasonally coherent calibration model N. Samal et al. 10.1080/15715124.2023.2218094
26. Improving Subseasonal-to-Seasonal forecasts in predicting the occurrence of extreme precipitation events over the contiguous U.S. using machine learning models L. Zhang et al. 10.1016/j.atmosres.2022.106502
27. Improving Precipitation Forecasts by Generating Ensembles through Postprocessing D. Shrestha et al. 10.1175/MWR-D-14-00329.1
28. Power transformation of variables for post-processing precipitation forecasts: Regionally versus locally optimized parameter values Y. Du et al. 10.1016/j.jhydrol.2022.127912
29. A real‐time pluvial flood forecasting system for Castries, St. Lucia J. René et al. 10.1111/jfr3.12205
30. A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data J. Lerat et al. 10.1016/j.jhydrol.2020.125129
31. pyNMME: A python toolkit to retrieve, calibrate and verify seasonal precipitation forecasts Z. Huang & T. Zhao 10.1016/j.envsoft.2023.105732
32. An evaluation of daily precipitation from a regional atmospheric reanalysis over Australia S. Acharya et al. 10.5194/hess-23-3387-2019
33. Analyzing the uncertainty of ensemble-based gridded observations in land surface simulations and drought assessment A. Ahmadalipour & H. Moradkhani 10.1016/j.jhydrol.2017.10.059
34. OpenForecast v2: Development and Benchmarking of the First National-Scale Operational Runoff Forecasting System in Russia G. Ayzel 10.3390/hydrology8010003
35. A comprehensive implementation of the log, Box-Cox and log-sinh transformations for skewed and censored precipitation data Z. Huang et al. 10.1016/j.jhydrol.2023.129347
36. A dialogue‐based weather forecast: adapting language to end‐users to improve communication A. Sivle & T. Aamodt 10.1002/wea.3439
37. Machine Learning Approaches to Improve North American Precipitation Forecasts C. Sengoz et al. 10.1109/ACCESS.2023.3309054
38. Using the Schaake shuffle when calibrating ensemble means can be problematic D. Shrestha et al. 10.1016/j.jhydrol.2020.124991
39. Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks A. Akbari Asanjan et al. 10.1029/2018JD028375
40. Improving Ensemble Forecasting Using Total Least Squares and Lead-Time Dependent Bias Correction A. Jabbari & D. Bae 10.3390/atmos11030300
41. Improving medium-range streamflow forecasts over South Korea with a dual-encoder transformer model D. Lee & K. Ahn 10.1016/j.jenvman.2024.122114
42. A Bayesian modelling approach to forecasting short-term reference crop evapotranspiration from GCM outputs T. Zhao et al. 10.1016/j.agrformet.2019.02.003
43. Impact of Lightning Data Assimilation on the Short-Term Precipitation Forecast over the Central Mediterranean Sea R. Torcasio et al. 10.3390/rs13040682
44. The challenge of forecasting high streamflows 1–3 months in advance with lagged climate indices in southeast Australia J. Bennett et al. 10.5194/nhess-14-219-2014
45. Probabilistic Forecast of Ecological Drought in Rivers Based on Numerical Weather Forecast from S2S Dataset C. Cai et al. 10.3390/w16040579
46. Attributing correlation skill of dynamical GCM precipitation forecasts to statistical ENSO teleconnection using a set-theory-based approach T. Zhao et al. 10.5194/hess-25-5717-2021
47. Downscaled numerical weather predictions can improve forecasts of sugarcane irrigation indices A. Schepen et al. 10.1016/j.compag.2024.109009
48. Impact of Assimilating Advanced Himawari Imager Channel 16 Data on Precipitation Prediction over the Haihe River Basin H. Ouyang et al. 10.3390/atmos12101253
49. A seven-parameter Bernoulli-Gamma-Gaussian model to calibrate subseasonal to seasonal precipitation forecasts Z. Huang et al. 10.1016/j.jhydrol.2022.127896
50. Improving Probabilistic Quantitative Precipitation Forecasts Using Short Training Data through Artificial Neural Networks M. Ghazvinian et al. 10.1175/JHM-D-22-0021.1
51. A method for preferential selection of dates in the Schaake shuffle approach to constructing spatiotemporal forecast fields of temperature and precipitation M. Scheuerer et al. 10.1002/2016WR020133
52. Statistical post-processing of numerical weather prediction data using distribution-based scaling for wind energy A. Rangaraj et al. 10.1177/0309524X241238353
53. Improving the heavy rainfall forecasting using a weighted deep learning model Y. Chen et al. 10.3389/fenvs.2023.1116672
54. Inter-comparison between retrospective ensemble streamflow forecasts using meteorological inputs from ECMWF and NOAA/ESRL in the Hudson River sub-basins during Hurricane Irene (2011) F. Saleh et al. 10.2166/nh.2018.182
55. Evaluating post-processing approaches for monthly and seasonal streamflow forecasts F. Woldemeskel et al. 10.5194/hess-22-6257-2018
56. Multivariate—Intervariable, Spatial, and Temporal—Bias Correction* M. Vrac & P. Friederichs 10.1175/JCLI-D-14-00059.1
57. Differing roles of base and fast flow in ensemble seasonal streamflow forecasting: An experimental investigation Z. Huang et al. 10.1016/j.jhydrol.2020.125272
58. Sub-daily temporal reconstruction of extreme precipitation events using NWP model simulations V. Bližňák et al. 10.1016/j.atmosres.2019.03.019
59. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. 10.1002/wat2.1246
60. Estimating daily precipitation climatology by postprocessing high‐resolution reanalysis data Y. Du et al. 10.1002/joc.8079
61. Extending a joint probability modelling approach for post-processing ensemble precipitation forecasts from numerical weather prediction models P. Zhao et al. 10.1016/j.jhydrol.2021.127285
62. An improved meta-Gaussian distribution model for post-processing of precipitation forecasts by censored maximum likelihood estimation W. Li et al. 10.1016/j.jhydrol.2019.04.073
63. 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
64. A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction A. Wright et al. 10.5194/hess-21-3827-2017
65. Describing the impacts of the extreme weather event on plants communities in Cibodas Botanic Gardens I. Hidayat 10.1088/1755-1315/1092/1/012004
66. Statistical Bias Correction of Precipitation Forecasts Based on Quantile Mapping on the Sub-Seasonal to Seasonal Scale X. Li et al. 10.3390/rs15071743
67. 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
68. Spatial mode-based calibration (SMoC) of forecast precipitation fields from numerical weather prediction models P. Zhao et al. 10.1016/j.jhydrol.2022.128432
69. Adapting subseasonal-to-seasonal (S2S) precipitation forecast at watersheds for hydrologic ensemble streamflow forecasting with a machine learning-based post-processing approach L. Zhang et al. 10.1016/j.jhydrol.2024.130643
70. How do I know if I’ve improved my continental scale flood early warning system? H. Cloke et al. 10.1088/1748-9326/aa625a
71. Probabilistic Conditioning and Recalibration of an Event-Based Flood Forecasting Model Using Real-Time Streamflow Observations K. Bahramian et al. 10.1061/(ASCE)HE.1943-5584.0002236
72. Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. 10.3390/w16101438
73. A national flood awareness system for ungauged catchments in complex topography: The case of development, communication and evaluation in New Zealand C. Cattoën et al. 10.1111/jfr3.12864
74. An integrated error parameter estimation and lag-aware data assimilation scheme for real-time flood forecasting Y. Li et al. 10.1016/j.jhydrol.2014.08.009
75. Reliable hourly streamflow forecasting with emphasis on ephemeral rivers M. Li et al. 10.1016/j.jhydrol.2020.125739
76. Achieving effective calibration of precipitation forecasts over a continental scale Q. Yang et al. 10.1016/j.ejrh.2021.100818
77. OpenForecast: An Assessment of the Operational Run in 2020–2021 G. Ayzel & D. Abramov 10.3390/geosciences12020067
78. Post-processing of hydrological model simulations using the convolutional neural network and support vector regression S. Liu et al. 10.2166/nh.2022.004
79. Hydrological responses to climate change in Yarlung Zangbo River basin, Southwest China W. Xuan et al. 10.1016/j.jhydrol.2020.125761
80. An approach for improving the capability of a coupled meteorological and hydrological model for rainfall and flood forecasts H. Nguyen & D. Bae 10.1016/j.jhydrol.2019.124014
81. 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
82. Calibration and quantifying uncertainty of daily water quality forecasts for large lakes with a Bayesian joint probability modelling approach Z. Peng et al. 10.1016/j.watres.2020.116162
83. On the Joint Calibration of Multivariate Seasonal Climate Forecasts from GCMs A. Schepen et al. 10.1175/MWR-D-19-0046.1
84. Calibrating Hourly Precipitation Forecasts with Daily Observations C. Cattoën et al. 10.1175/JHM-D-19-0246.1
85. Two novel error-updating model frameworks for short-to-medium range streamflow forecasting using bias-corrected rainfall inputs: Development and comparative assessment A. Khatun et al. 10.1016/j.jhydrol.2023.129199
86. How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts? T. Zhao et al. 10.1175/JCLI-D-16-0652.1
87. Multivariate ensemble Model Output Statistics using empirical copulas D. Wilks 10.1002/qj.2414
88. A new scheme for multivariate, multisite weather generator with inter-variable, inter-site dependence and inter-annual variability based on empirical copula approach X. Li & V. Babovic 10.1007/s00382-018-4249-5
89. Evaluation of ERA5 and ERA5-Land reanalysis precipitation datasets over Spain (1951–2020) J. Gomis-Cebolla et al. 10.1016/j.atmosres.2023.106606
90. Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques A. Wright et al. 10.1002/2017WR020442
91. Ensemble forecasting of sub-seasonal to seasonal streamflow by a Bayesian joint probability modelling approach T. Zhao et al. 10.1016/j.jhydrol.2016.07.040
92. Improving categorical and continuous accuracy of precipitation forecasts by integrating Empirical Quantile Mapping and Bernoulli-Gamma-Gaussian distribution L. Li et al. 10.1016/j.atmosres.2023.107133
93. Improved error modelling for streamflow forecasting at hourly time steps by splitting hydrographs into rising and falling limbs M. Li et al. 10.1016/j.jhydrol.2017.10.057
94. Adapting rainfall bias-corrections to improve hydrological simulations generated from climate model forcings D. Robertson et al. 10.1016/j.jhydrol.2023.129322
95. Comparative Evaluation of Three Schaake Shuffle Schemes in Postprocessing GEFS Precipitation Ensemble Forecasts L. Wu et al. 10.1175/JHM-D-17-0054.1
96. Prediction of daily rainfall by a hybrid wavelet-season-neuro technique A. Altunkaynak & T. Nigussie 10.1016/j.jhydrol.2015.07.046
97. Simplified Approach to Mixed-Integer Chance-Constrained Optimization with Ensemble Streamflow Forecasts for Risk-Based Dam Operation T. Ng et al. 10.1061/JWRMD5.WRENG-5885
98. Relating anomaly correlation to lead time: Clustering analysis of CFSv2 forecasts of summer precipitation in China T. Zhao et al. 10.1002/2017JD027018
99. Assessment and modelling of uncertainty in precipitation forecasts from TIGGE using fuzzy probability and Bayesian theory C. Cai et al. 10.1016/j.jhydrol.2019.123995
100. Evaluation of TIGGE Daily Accumulated Precipitation Forecasts over the Qu River Basin, China L. Liu et al. 10.1007/s13351-019-8096-z
101. A New Hybrid Framework for Error Correction and Uncertainty Analysis of Precipitation Forecasts with Combined Postprocessors C. Cai et al. 10.3390/w14193072
102. Ensemble forecasting of short‐term system scale irrigation demands using real‐time flow data and numerical weather predictions K. Perera et al. 10.1002/2015WR018532
103. Development of a national 7-day ensemble streamflow forecasting service for Australia H. Hapuarachchi et al. 10.5194/hess-26-4801-2022
104. Deep-learning post-processing of short-term station precipitation based on NWP forecasts Q. Liu et al. 10.1016/j.atmosres.2023.107032
105. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments A. Schepen et al. 10.5194/hess-22-1615-2018
106. Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment S. Jha et al. 10.5194/hess-22-1957-2018
107. Multi‐Task Deep Learning of Daily Streamflow and Water Temperature J. Sadler et al. 10.1029/2021WR030138
108. A Seasonally Coherent Calibration (SCC) Model for Postprocessing Numerical Weather Predictions Q. Wang et al. 10.1175/MWR-D-19-0108.1
109. 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
110. Evaluation and Statistical Post‐Processing of Two Precipitation Reforecast Products During Summer in the Mainland of China W. Li et al. 10.1029/2022JD036606
111. Bias correction of ensemble precipitation forecasts in the improvement of summer streamflow prediction skill C. Yang et al. 10.1016/j.jhydrol.2020.124955
112. Seasonal rainfall totals of Australian stations can be modelled with distributions from the Tweedie family M. Hasan & P. Dunn 10.1002/joc.4194