Articles | Volume 30, issue 3
https://doi.org/10.5194/hess-30-629-2026
https://doi.org/10.5194/hess-30-629-2026
Research article
 | 
04 Feb 2026
Research article |  | 04 Feb 2026

When physics gets in the way: an entropy-based evaluation of conceptual constraints in hybrid hydrological models

Manuel Álvarez Chaves, Eduardo Acuña Espinoza, Uwe Ehret, and Anneli Guthke

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Short summary
This study evaluates hybrid hydrological models combining physics-based and data-driven components, using Information Theory to measure their relative contributions. When testing conceptual models with Long Short-Term Memory (LSTM) networks that adjust parameters over time, we found performance primarily comes from the data-driven component, with physics constraints adding minimal value. We propose a quantitative tool to analyse this behaviour and suggest a workflow for diagnosing hybrid models.
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