Articles | Volume 29, issue 11
https://doi.org/10.5194/hess-29-2361-2025
https://doi.org/10.5194/hess-29-2361-2025
Technical note
 | 
04 Jun 2025
Technical note |  | 04 Jun 2025

Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?

Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark

Data sets

A large-sample watershed-scale hydrometeorological dataset for the contiguous USA A. Newman et al. https://doi.org/10.5065/D6MW2F4D

Catchment attributes for large-sample studies N. Addor et al. https://doi.org/10.5065/D6G73C3Q

Data from "A brief analysis of conceptual model structure uncertainty using 36 models and 559 catchments" W. Knoben et al. https://doi.org/10.5523/BRIS.2ZUTXH2QEEP6Y2CY6SCWGK9EQJ

Model code and software

CH-Earth/multi-model-mosaic-paper: Peer review release Wouter J. M. Knoben https://doi.org/10.5281/zenodo.13515769

gumboot: Bootstrap Analyses of Sampling Uncertainty in Goodness-of-Fit statistics M. Clark and K. Shook https://github.com/CH-Earth/gumboot

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Short summary
Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.
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