Articles | Volume 16, issue 3
https://doi.org/10.5194/hess-16-815-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-16-815-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
14 Mar 2012
Research article |
| 14 Mar 2012
An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions
M. He
Department of Civil and Environmental Engineering, University of California, Los Angeles, California, USA
currently at: Office of Hydrologic Development, NOAA National Weather Service, Silver Spring, Maryland, USA
currently at: Riverside Technology, Inc., Fort Collins, Colorado, USA
T. S. Hogue
Department of Civil and Environmental Engineering, University of California, Los Angeles, California, USA
S. A. Margulis
Department of Civil and Environmental Engineering, University of California, Los Angeles, California, USA
K. J. Franz
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, Iowa, USA
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Cited
25 citations as recorded by crossref.
- Remote sensing of drought: Progress, challenges and opportunities A. AghaKouchak et al. https://doi.org/10.1002/2014RG000456
- Assessing 32-Day Hydrological Ensemble Forecasts in the Lake Champlain–Richelieu River Watershed M. Abaza et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001983
- Assimilation of Ground and Satellite Snow Observations in a Distributed Hydrologic Model for Water Supply Forecasting P. Micheletty et al. https://doi.org/10.1111/1752-1688.12975
- Review of Snow Data Assimilation Methods for Hydrological, Land Surface, Meteorological and Climate Models: Results from a COST HarmoSnow Survey J. Helmert et al. https://doi.org/10.3390/geosciences8120489
- Sensitivity of hydrological ensemble forecasts to different sources and temporal resolutions of probabilistic quantitative precipitation forecasts: flash flood case studies in the Cévennes‐Vivarais region (Southern France) R. Marty et al. https://doi.org/10.1002/hyp.9543
- Assimilation of stream discharge for flood forecasting: Updating a semidistributed model with an integrated data assimilation scheme Y. Li et al. https://doi.org/10.1002/2014WR016667
- Coupling duo-assimilation to hydrological model to enhance flood forecasting D. Dang & T. Anh https://doi.org/10.1080/23249676.2023.2201475
- Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil F. Fan et al. https://doi.org/10.1016/j.ejrh.2015.05.012
- Probabilistic Forecasts of Snow Water Equivalent and Runoff in Mountainous Areas* S. Jörg-Hess et al. https://doi.org/10.1175/JHM-D-14-0193.1
- Evaluation of Model Parameter Convergence when Using Data Assimilation for Soil Moisture Estimation G. Dumedah & J. Walker https://doi.org/10.1175/JHM-D-12-0175.1
- Calibration of a distributed snow model using MODIS snow covered area data K. Franz & L. Karsten https://doi.org/10.1016/j.jhydrol.2013.04.026
- Potential Changes in Runoff of California’s Major Water Supply Watersheds in the 21st Century M. He et al. https://doi.org/10.3390/w11081651
- Hydro Genome Mapping: An Approach for the Diagnosis, Evaluation and Improving Prediction Capability of Hydro-Meteorological Models G. Dumedah https://doi.org/10.1007/s11269-019-02336-2
- Assimilating snow observations to snow interception process simulations Z. Lv & J. Pomeroy https://doi.org/10.1002/hyp.13720
- Review of the Kalman-type hydrological data assimilation L. Sun et al. https://doi.org/10.1080/02626667.2015.1127376
- Assimilation of AMSR-E snow water equivalent data in a spatially-lumped snow model D. Dziubanski & K. Franz https://doi.org/10.1016/j.jhydrol.2016.05.046
- Assessment of SWE data assimilation for ensemble streamflow predictions K. Franz et al. https://doi.org/10.1016/j.jhydrol.2014.07.008
- The Science of NOAA's Operational Hydrologic Ensemble Forecast Service J. Demargne et al. https://doi.org/10.1175/BAMS-D-12-00081.1
- An integrated error parameter estimation and lag-aware data assimilation scheme for real-time flood forecasting Y. Li et al. https://doi.org/10.1016/j.jhydrol.2014.08.009
- Combined assimilation of streamflow and snow water equivalent for mid-term ensemble streamflow forecasts in snow-dominated regions J. Bergeron et al. https://doi.org/10.5194/hess-20-4375-2016
- Assessment of model behavior and acceptable forcing data uncertainty in the context of land surface soil moisture estimation G. Dumedah & J. Walker https://doi.org/10.1016/j.advwatres.2017.01.001
- Verification of Ensemble Water Supply Forecasts for Sierra Nevada Watersheds M. He et al. https://doi.org/10.3390/hydrology3040035
- A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification V. Tran et al. https://doi.org/10.1029/2019WR025727
- Closing the Gaps in Our Knowledge of the Hydrological Cycle over Land: Conceptual Problems W. Lahoz & G. De Lannoy https://doi.org/10.1007/s10712-013-9221-7
- Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States C. Huang et al. https://doi.org/10.5194/hess-21-635-2017
25 citations as recorded by crossref.
- Remote sensing of drought: Progress, challenges and opportunities A. AghaKouchak et al. https://doi.org/10.1002/2014RG000456
- Assessing 32-Day Hydrological Ensemble Forecasts in the Lake Champlain–Richelieu River Watershed M. Abaza et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001983
- Assimilation of Ground and Satellite Snow Observations in a Distributed Hydrologic Model for Water Supply Forecasting P. Micheletty et al. https://doi.org/10.1111/1752-1688.12975
- Review of Snow Data Assimilation Methods for Hydrological, Land Surface, Meteorological and Climate Models: Results from a COST HarmoSnow Survey J. Helmert et al. https://doi.org/10.3390/geosciences8120489
- Sensitivity of hydrological ensemble forecasts to different sources and temporal resolutions of probabilistic quantitative precipitation forecasts: flash flood case studies in the Cévennes‐Vivarais region (Southern France) R. Marty et al. https://doi.org/10.1002/hyp.9543
- Assimilation of stream discharge for flood forecasting: Updating a semidistributed model with an integrated data assimilation scheme Y. Li et al. https://doi.org/10.1002/2014WR016667
- Coupling duo-assimilation to hydrological model to enhance flood forecasting D. Dang & T. Anh https://doi.org/10.1080/23249676.2023.2201475
- Verification of inflow into hydropower reservoirs using ensemble forecasts of the TIGGE database for large scale basins in Brazil F. Fan et al. https://doi.org/10.1016/j.ejrh.2015.05.012
- Probabilistic Forecasts of Snow Water Equivalent and Runoff in Mountainous Areas* S. Jörg-Hess et al. https://doi.org/10.1175/JHM-D-14-0193.1
- Evaluation of Model Parameter Convergence when Using Data Assimilation for Soil Moisture Estimation G. Dumedah & J. Walker https://doi.org/10.1175/JHM-D-12-0175.1
- Calibration of a distributed snow model using MODIS snow covered area data K. Franz & L. Karsten https://doi.org/10.1016/j.jhydrol.2013.04.026
- Potential Changes in Runoff of California’s Major Water Supply Watersheds in the 21st Century M. He et al. https://doi.org/10.3390/w11081651
- Hydro Genome Mapping: An Approach for the Diagnosis, Evaluation and Improving Prediction Capability of Hydro-Meteorological Models G. Dumedah https://doi.org/10.1007/s11269-019-02336-2
- Assimilating snow observations to snow interception process simulations Z. Lv & J. Pomeroy https://doi.org/10.1002/hyp.13720
- Review of the Kalman-type hydrological data assimilation L. Sun et al. https://doi.org/10.1080/02626667.2015.1127376
- Assimilation of AMSR-E snow water equivalent data in a spatially-lumped snow model D. Dziubanski & K. Franz https://doi.org/10.1016/j.jhydrol.2016.05.046
- Assessment of SWE data assimilation for ensemble streamflow predictions K. Franz et al. https://doi.org/10.1016/j.jhydrol.2014.07.008
- The Science of NOAA's Operational Hydrologic Ensemble Forecast Service J. Demargne et al. https://doi.org/10.1175/BAMS-D-12-00081.1
- An integrated error parameter estimation and lag-aware data assimilation scheme for real-time flood forecasting Y. Li et al. https://doi.org/10.1016/j.jhydrol.2014.08.009
- Combined assimilation of streamflow and snow water equivalent for mid-term ensemble streamflow forecasts in snow-dominated regions J. Bergeron et al. https://doi.org/10.5194/hess-20-4375-2016
- Assessment of model behavior and acceptable forcing data uncertainty in the context of land surface soil moisture estimation G. Dumedah & J. Walker https://doi.org/10.1016/j.advwatres.2017.01.001
- Verification of Ensemble Water Supply Forecasts for Sierra Nevada Watersheds M. He et al. https://doi.org/10.3390/hydrology3040035
- A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification V. Tran et al. https://doi.org/10.1029/2019WR025727
- Closing the Gaps in Our Knowledge of the Hydrological Cycle over Land: Conceptual Problems W. Lahoz & G. De Lannoy https://doi.org/10.1007/s10712-013-9221-7
- Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States C. Huang et al. https://doi.org/10.5194/hess-21-635-2017
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