Articles | Volume 29, issue 11
https://doi.org/10.5194/hess-29-2407-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-2407-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jun 2025
Research article |
| 10 Jun 2025
| 10 Jun 2025
Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting
Peyman Abbaszadeh
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Hydrologic Modeling and Assimilation Lab, Portland State University, Portland, OR, USA
Fatemeh Gholizadeh
Department of Civil and Environmental Engineering, Hydrologic Modeling and Assimilation Lab, Portland State University, Portland, OR, USA
Keyhan Gavahi
Center for Complex Hydrosystems Research, Department of Civil, Construction and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
Hamid Moradkhani
Center for Complex Hydrosystems Research, Department of Civil, Construction and Environmental Engineering, University of Alabama, Tuscaloosa, AL, USA
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Short summary
The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.
The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems...
