Articles | Volume 17, issue 9
https://doi.org/10.5194/hess-17-3499-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-3499-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
13 Sep 2013
Research article |
| 13 Sep 2013
Simultaneous estimation of model state variables and observation and forecast biases using a two-stage hybrid Kalman filter
V. R. N. Pauwels
Department of Civil Engineering, Monash University, Clayton, Victoria, Australia
G. J. M. De Lannoy
NASA Goddard Space Flight Center, Greenbelt, MD, USA
H.-J. Hendricks Franssen
Forschungszentrum Jülich GmbH, Agrosphere (IBG-3), Jülich, Germany
H. Vereecken
Forschungszentrum Jülich GmbH, Agrosphere (IBG-3), Jülich, Germany
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- An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space S. Kumar et al. 10.1029/2022MS003259
- Bias-aware data assimilation in integrated hydrological modelling M. Ridler et al. 10.2166/nh.2017.117
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- Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review Y. Li et al. 10.3390/rs8060456
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- Data assimilation of surface displacements to improve geomechanical parameters of gas storage reservoirs C. Zoccarato et al. 10.1002/2015JB012090
- Soil hydrology: Recent methodological advances, challenges, and perspectives H. Vereecken et al. 10.1002/2014WR016852
- Comparison of microwave remote sensing and land surface modeling for surface soil moisture climatology estimation J. Dong et al. 10.1016/j.rse.2020.111756
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- Investigating the application of Kalman Filters for real-time accountancy in fusion fuel cycles H. Flynn & G. Larsen 10.1016/j.fusengdes.2022.113037
- Improving Robustness of Hydrologic Ensemble Predictions Through Probabilistic Pre‐ and Post‐Processing in Sequential Data Assimilation S. Wang et al. 10.1002/2018WR022546
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- 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
- 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
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