86 citations as recorded by crossref.

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30. Nonparametric Data Assimilation Scheme for Land Hydrological Applications M. Khaki et al. 10.1029/2018WR022854
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37. A regional coupled approach to water cycle prediction during winter 2013/14 in the United Kingdom H. Lewis & S. Dadson 10.1002/hyp.14438
38. 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
39. Sensitivity analysis of the hyperparameters of an ensemble Kalman filter application on a semi-distributed hydrological model for streamflow forecasting B. Sabzipour et al. 10.1016/j.jhydrol.2023.130251
40. Assimilating water level observations with the ensemble optimal interpolation scheme into a rainfall‐runoff‐inundation model: A repository‐based dynamic covariance matrix generation approach M. Khaniya et al. 10.1111/jfr3.13017
41. Accounting for three sources of uncertainty in ensemble hydrological forecasting A. Thiboult et al. 10.5194/hess-20-1809-2016
42. A Bayesian consistent dual ensemble Kalman filter for state-parameter estimation in subsurface hydrology B. Ait-El-Fquih et al. 10.5194/hess-20-3289-2016
43. The role of rating curve uncertainty in real‐time flood forecasting D. Ocio et al. 10.1002/2016WR020225
44. Sequential Data Assimilation for Streamflow Forecasting: Assessing the Sensitivity to Uncertainties and Updated Variables of a Conceptual Hydrological Model at Basin Scale G. Piazzi et al. 10.1029/2020WR028390
45. Recursively updating the error forecasting scheme of a complementary modelling framework for improved reservoir inflow forecasts A. Gragne et al. 10.1016/j.jhydrol.2015.05.039
46. Assessment of SWE data assimilation for ensemble streamflow predictions K. Franz et al. 10.1016/j.jhydrol.2014.07.008
47. A physically based and machine learning hybrid approach for accurate rainfall-runoff modeling during extreme typhoon events C. Young et al. 10.1016/j.asoc.2016.12.052
48. A coupled ensemble filtering and probabilistic collocation approach for uncertainty quantification of hydrological models Y. Fan et al. 10.1016/j.jhydrol.2015.09.035
49. Combined assimilation of streamflow and snow water equivalent for mid-term ensemble streamflow forecasts in snow-dominated regions J. Bergeron et al. 10.5194/hess-20-4375-2016
50. Variational assimilation of streamflow data in distributed flood forecasting G. Ercolani & F. Castelli 10.1002/2016WR019208
51. Improving flood forecasting using an input correction method in urban models in poorly gauged areas M. Fava et al. 10.1080/02626667.2020.1729984
52. Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations M. Trudel et al. 10.1016/j.jhydrol.2014.03.072
53. A review of applications of satellite SAR, optical, altimetry and DEM data for surface water modelling, mapping and parameter estimation Z. Musa et al. 10.5194/hess-19-3755-2015
54. Nonparametric catchment clustering using the data depth function S. Singh et al. 10.1080/02626667.2016.1168927
55. Validation of a national hydrological model H. McMillan et al. 10.1016/j.jhydrol.2016.07.043
56. Review of the Kalman-type hydrological data assimilation L. Sun et al. 10.1080/02626667.2015.1127376
57. Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter S. Wang et al. 10.1016/j.jhydrol.2017.09.052
58. RBFNN Versus Empirical Models for Lag Time Prediction in Tropical Humid Rivers M. Seyam et al. 10.1007/s11269-016-1518-0
59. The Met Office Operational Soil Moisture Analysis System B. Gómez et al. 10.3390/rs12223691
60. Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. 10.1029/2021WR031649
61. Discharge Estimation via Assimilation of Multisatellite-Based Discharge Products: Case Study Over the Amazon Basin C. Emery et al. 10.1109/LGRS.2020.3020285
62. Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models M. Mazzoleni et al. 10.1016/j.advwatres.2015.07.004
63. Assimilation of soil moisture and streamflow observations to improve flood forecasting with considering runoff routing lags S. Meng et al. 10.1016/j.jhydrol.2017.05.024
64. Underlying Fundamentals of Kalman Filtering for River Network Modeling C. Emery et al. 10.1175/JHM-D-19-0084.1
65. State updating in a distributed hydrological model by ensemble Kalman filtering with error estimation J. Gong et al. 10.1016/j.jhydrol.2023.129450
66. 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
67. Review of assimilating GRACE terrestrial water storage data into hydrological models: Advances, challenges and opportunities S. Soltani et al. 10.1016/j.earscirev.2020.103487
68. Assessing model state and forecasts variation in hydrologic data assimilation J. Samuel et al. 10.1016/j.jhydrol.2014.03.048
69. Ensemble streamflow data assimilation using WRF-Hydro and DART: novel localization and inflation techniques applied to Hurricane Florence flooding M. El Gharamti et al. 10.5194/hess-25-5315-2021
70. Development of the consider cubature Kalman filter for state estimation of hydrological models with parameter uncertainty Y. Sun et al. 10.1016/j.jhydrol.2023.130080
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75. Parameter uncertainty and temporal dynamics of sensitivity for hydrologic models: A hybrid sequential data assimilation and probabilistic collocation method Y. Fan et al. 10.1016/j.envsoft.2016.09.012
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79. Comparing and combining physically-based and empirically-based approaches for estimating the hydrology of ungauged catchments D. Booker & R. Woods 10.1016/j.jhydrol.2013.11.007
80. Comparison of Sequential and Variational Streamflow Assimilation Techniques for Short-Term Hydrological Forecasting M. Abaza et al. 10.1061/(ASCE)HE.1943-5584.0001013
81. Assimilation of citizen science data in snowpack modeling using a new snow data set: Community Snow Observations R. Crumley et al. 10.5194/hess-25-4651-2021
82. Analysis of rainfall intensity impact on the lag time estimation in tropical humid rivers e. Seyam 10.21833/ijaas.2017.010.003
83. Improving Treatment of Noise Specification of Kalman Filtering for State Updating of Hydrological Models: Combining the Strengths of the Interacting Multiple Model Method and Cubature Kalman Filter Y. Sun et al. 10.1029/2022WR033635
84. The streamflow estimation using the Xinanjiang rainfall runoff model and dual state-parameter estimation method H. Lü et al. 10.1016/j.jhydrol.2012.12.011
85. Impact of improved meteorological forcing, profile of soil hydraulic conductivity and data assimilation on an operational Hydrological Ensemble Forecast System over France M. Coustau et al. 10.1016/j.jhydrol.2015.04.022
86. Assimilation of soil moisture and streamflow observations to improve flood forecasting with considering runoff routing lags S. Meng et al. 10.1016/j.jhydrol.2017.05.024