Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 26, issue 5
Articles | Volume 26, issue 5
https://doi.org/10.5194/nhess-26-2353-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-2353-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 5
Research article
 | 
26 May 2026
Research article |  | 26 May 2026

Enhancing hydrological hazard early warning: a 60 d streamflow forecasting framework integrating deep learning and process-based modeling

Zhijie Liu, Hanbo Yang, and Dawen Yang

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Short summary
Reliable medium- and long-term streamflow forecasts are essential for hazard early warning. We develop a 60-day forecasting framework that corrects precipitation from numerical weather prediction models, utilizes a physical hydrologic model and mitigates systematic simulation errors. Applied to the Upper Yangtze River Basin, it yields practical 60-day forecasts with good accuracy, providing a robust tool for proactive decision making in hazard mitigation to ensure regional water security.
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