Comparing multi-model mosaic and multi-model combination methods to simulate streamflow across the contiguous USA

Thébault, Cyril; Knoben, Wouter J. M.; Addor, Nans; Newman, Andrew J.; Spieler, Diana; Vásquez, Nicolás A.; Song, Yalan; Gründemann, Gaby J.; Carney, Shaun; Kumar, Mukesh; van Werkhoven, Katie; Shen, Chaopeng; Wood, Andrew W.; Clark, Martyn P.

doi:10.5194/hess-30-3945-2026

Articles | Volume 30, issue 12

https://doi.org/10.5194/hess-30-3945-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-30-3945-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 30, issue 12

Research article

|

29 Jun 2026

Research article |

| 29 Jun 2026

Comparing multi-model mosaic and multi-model combination methods to simulate streamflow across the contiguous USA

Cyril Thébault, Wouter J. M. Knoben, Nans Addor, Andrew J. Newman, Diana Spieler, Nicolás A. Vásquez, Yalan Song, Gaby J. Gründemann, Shaun Carney, Mukesh Kumar, Katie van Werkhoven, Chaopeng Shen, Andrew W. Wood, and Martyn P. Clark

Data sets

CAMELS: Catchment Attributes and MEteorology for Large-sample Studies A. J. Newman et al. https://doi.org/10.5065/D6MW2F4D

Model code and software

CyrilThebault/FUSE-MMComparison-paper: FUSE-MMComparison-paper v1.0 (v1.0) C. Thébault https://doi.org/10.5281/zenodo.20500212

CyrilThebault/fuse: FUSE version for multi-model comparison paper (v1.0_MMpaper) C. Thébault et al. https://doi.org/10.5281/zenodo.20500504

Short summary

Reliable river flow prediction guide water supply planning and flood protection. We tested whether selecting or combining multiple models improves accuracy compared with a single model. 78 models were used and tested in 559 river basins across the United States. A carefully chosen single model nearly matched more complex multi-model approaches, while combining models gave slightly higher accuracy and lower uncertainty. However, no approach worked best everywhere.