Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts

Matthews, Gwyneth; Cloke, Hannah L.; Dance, Sarah L.; Prudhomme, Christel

doi:10.5194/hess-29-6157-2025

Articles | Volume 29, issue 21

https://doi.org/10.5194/hess-29-6157-2025

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

https://doi.org/10.5194/hess-29-6157-2025

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

Articles | Volume 29, issue 21

Research article

|

11 Nov 2025

Research article |

| 11 Nov 2025

Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts

Gwyneth Matthews, Hannah L. Cloke, Sarah L. Dance, and Christel Prudhomme

Data sets

River discharge and related forecasted data from the European Flood Awareness System, v4.0 C. Barnard et al. https://doi.org/10.24381/cds.9f696a7a

LISFLOOD static and parameter maps for Europe Margarita Choulga et al. http://data.europa.eu/89h/f572c443-7466-4adf-87aa-c0847a169f23

Model code and software

Code accompaniment for "Error-correction across gauged and ungauged locations: A data assimilation-inspired approach to post-processing river discharge forecasts" (1.0) Gwyneth Matthews https://doi.org/10.5281/zenodo.17256468

Short summary

Forecasts provide information crucial for managing floods and for water resource planning, but they often have errors. “Post-processing” reduces these errors but is usually only applied at river gauges, leaving areas without gauges uncorrected. We developed a new method that uses spatial information contained within the forecast to spread information about the errors from gauged locations to ungauged areas. Our results show that the method successfully makes river forecasts more accurate.