Articles | Volume 29, issue 19
https://doi.org/10.5194/hess-29-4913-2025
https://doi.org/10.5194/hess-29-4913-2025
Research article
 | 
01 Oct 2025
Research article |  | 01 Oct 2025

Combining uncertainty quantification and entropy-inspired concepts into a single objective function for rainfall-runoff model calibration

Alonso Pizarro, Demetris Koutsoyiannis, and Alberto Montanari

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Short summary
We introduce the ratio of uncertainty to mutual information (RUMI), a new metric to improve rainfall-runoff simulations. RUMI better captures the link between observed and simulated stream flows by considering uncertainty at a core computation step. Tested on 99 catchments and with the GR4J model, it outperforms traditional metrics by providing more reliable and consistent results. RUMI paves the way for more accurate hydrological predictions.
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