Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting

Abbaszadeh, Peyman; Gholizadeh, Fatemeh; Gavahi, Keyhan; Moradkhani, Hamid

doi:https://doi.org/10.5194/hess-29-2407-2025

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.

https://doi.org/10.5194/hess-29-2407-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 29, issue 11

Research article

|

10 Jun 2025

Research article |

| 10 Jun 2025

Towards a robust hydrologic data assimilation system for hurricane-induced river flow forecasting

Peyman Abbaszadeh, Fatemeh Gholizadeh, Keyhan Gavahi, and Hamid Moradkhani

Supplement

https://doi.org/10.5194/hess-29-2407-2025-supplement

Model code and software

sac-sma NOAA-OWP https://github.com/NOAA-OWP/sac-sma

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.