Articles | Volume 16, issue 7
https://doi.org/10.5194/hess-16-2233-2012
© 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-16-2233-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Jul 2012
Research article |
| 23 Jul 2012
Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal scale of adjustment
H. Lee
NOAA, National Weather Service, Office of Hydrologic Development, Silver Spring, Maryland, USA
University Corporation for Atmospheric Research, Boulder, Colorado, USA
D.-J. Seo
NOAA, National Weather Service, Office of Hydrologic Development, Silver Spring, Maryland, USA
University Corporation for Atmospheric Research, Boulder, Colorado, USA
present address: Department of Civil Engineering, The University of Texas at Arlington, Arlington, TX 76019-0308, USA
Y. Liu
NOAA, National Weather Service, Office of Hydrologic Development, Silver Spring, Maryland, USA
Riverside Technology, Inc., Fort Collins, Colorado, USA
present address: Goddard Space Flight Center, National Aeronautics and Space Administration, Greenbelt, MD 20771, USA
V. Koren
NOAA, National Weather Service, Office of Hydrologic Development, Silver Spring, Maryland, USA
P. McKee
NOAA, National Weather Service, West Gulf River Forecast Center, Fort Worth, Texas, USA
R. Corby
NOAA, National Weather Service, West Gulf River Forecast Center, Fort Worth, Texas, USA
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40 citations as recorded by crossref.
- The suitability of remotely sensed soil moisture for improving operational flood forecasting N. Wanders et al. 10.5194/hess-18-2343-2014
- Improving high-resolution quantitative precipitation estimation via fusion of multiple radar-based precipitation products A. Rafieeinasab et al. 10.1016/j.jhydrol.2015.04.066
- Influence of spatial distribution of sensors and observation accuracy on the assimilation of distributed streamflow data in hydrological modelling M. Mazzoleni et al. 10.1080/02626667.2016.1247211
- Comparative evaluation of maximum likelihood ensemble filter and ensemble Kalman filter for real-time assimilation of streamflow data into operational hydrologic models A. Rafieeinasab et al. 10.1016/j.jhydrol.2014.06.052
- Improving streamflow predictions at ungauged locations with real-time updating: application of an EnKF-based state-parameter estimation strategy X. Xie et al. 10.5194/hess-18-3923-2014
- Assimilation of Images via Dictionary Learning-Based Sparsity Regularization Strategy: An Application for Retrieving Fluid Flows L. Li et al. 10.1109/TGRS.2021.3110799
- Remote sensing data assimilation A. Nair et al. 10.1080/02626667.2020.1761021
- Adaptive Conditional Bias-Penalized Kalman Filter for Improved Estimation of Extremes and Its Approximation for Reduced Computation H. Shen et al. 10.3390/hydrology9020035
- Improving the Forecast Performance of Hydrological Models Using the Cubature Kalman Filter and Unscented Kalman Filter Y. Sun et al. 10.1029/2022WR033580
- On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment M. Jay-Allemand et al. 10.5194/hess-24-5519-2020
- Adaptive period decomposition network with muti-scale temporal variation learning for water level prediction H. Wang et al. 10.1016/j.ejrh.2024.102120
- Assimilation of stream discharge for flood forecasting: Updating a semidistributed model with an integrated data assimilation scheme Y. Li et al. 10.1002/2014WR016667
- Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models M. Mazzoleni et al. 10.1016/j.advwatres.2015.07.004
- ISANet: Deep Neural Network Approximating Image Sequence Assimilation for Tracking Fluid Flows L. Li & J. Ma 10.1109/TGRS.2023.3334612
- Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations P. López López et al. 10.5194/hess-20-3059-2016
- Mean Field Bias-Aware State Updating via Variational Assimilation of Streamflow into Distributed Hydrologic Models H. Lee et al. 10.3390/forecast2040028
- Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities Y. Liu et al. 10.5194/hess-16-3863-2012
- Sensitivity‐Based Soil Moisture Assimilation for Improved Streamflow Forecast Using a Novel Forward Sensitivity Method (FSM) Approach R. Visweshwaran et al. 10.1029/2021WR031092
- State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy O. Rakovec et al. 10.5194/hess-16-3435-2012
- Unified Hydrological Flow Routing for Variational Data Assimilation and Model Predictive Control R. Montero et al. 10.1016/j.proeng.2016.07.488
- High-resolution modeling and prediction of urban floods using WRF-Hydro and data assimilation S. Kim et al. 10.1016/j.jhydrol.2021.126236
- Comparison of Deterministic and Probabilistic Variational Data Assimilation Methods Using Snow and Streamflow Data Coupled in HBV Model for Upper Euphrates Basin G. Uysal et al. 10.3390/geosciences13030089
- Multi-parametric variational data assimilation for hydrological forecasting R. Alvarado-Montero et al. 10.1016/j.advwatres.2017.09.026
- Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model R. Montero et al. 10.1016/j.advwatres.2016.04.011
- 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
- Improvement of operational flood forecasting through the assimilation of satellite observations and multiple river flow data F. Castelli & G. Ercolani 10.5194/piahs-373-167-2016
- Improving flood forecasting using conditional bias-aware assimilation of streamflow observations and dynamic assessment of flow-dependent information content H. Shen et al. 10.1016/j.jhydrol.2021.127247
- Variational assimilation of remotely sensed flood extents using a 2-D flood model X. Lai et al. 10.5194/hess-18-4325-2014
- Improving flood forecasting using conditional bias-penalized ensemble Kalman filter H. Lee et al. 10.1016/j.jhydrol.2019.05.072
- State updating in a distributed hydrological model by ensemble Kalman filtering with error estimation J. Gong et al. 10.1016/j.jhydrol.2023.129450
- Hybrid forecasting model for non-stationary daily runoff series: A case study in the Han River Basin, China T. Xie et al. 10.1016/j.jhydrol.2019.123915
- A weakly-constrained data assimilation approach to address rainfall-runoff model structural inadequacy in streamflow prediction H. Lee et al. 10.1016/j.jhydrol.2016.09.009
- Assimilation of hydrologic and hydrometeorological data into distributed hydrologic model: Effect of adjusting mean field bias in radar-based precipitation estimates H. Lee & D. Seo 10.1016/j.advwatres.2014.09.002
- Variational assimilation of streamflow data in distributed flood forecasting G. Ercolani & F. Castelli 10.1002/2016WR019208
- Flood modelling using synthesised citizen science urban streamflow observations M. Fava et al. 10.1111/jfr3.12498
- Assimilating in situ and radar altimetry data into a large-scale hydrologic-hydrodynamic model for streamflow forecast in the Amazon R. Paiva et al. 10.5194/hess-17-2929-2013
- SWAT‐Based Hydrological Data Assimilation System (SWAT‐HDAS): Description and Case Application to River Basin‐Scale Hydrological Predictions Y. Zhang et al. 10.1002/2017MS001144
- Utilizing satellite precipitation estimates for streamflow forecasting via adjustment of mean field bias in precipitation data and assimilation of streamflow observations H. Lee et al. 10.1016/j.jhydrol.2015.08.057
- Toward Discharge Estimation for Water Resources Management with a Semidistributed Model and Local Ensemble Kalman Filter Data Assimilation S. Wongchuig et al. 10.1061/(ASCE)HE.1943-5584.0002027
- Spatio‐Temporal Model Variance‐Covariance Approach to Assimilating Streamflow Observations Into a Distributed Landscape Water Balance Model S. Tian et al. 10.1029/2021WR031649
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- Comparison of Sequential and Variational Streamflow Assimilation Techniques for Short-Term Hydrological Forecasting M. Abaza et al. 10.1061/(ASCE)HE.1943-5584.0001013
- Improving water quality forecasting via data assimilation – Application of maximum likelihood ensemble filter to HSPF S. Kim et al. 10.1016/j.jhydrol.2014.09.051
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