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Hydrological model skill score and Revised R-Squared

Authors: Onyutha, Charles;

Hydrological model skill score and Revised R-Squared

Abstract

The publication "Onyutha C (2025) A multi-hydrological model ensemble prediction uncertainty estimation (e-PRUNE) framework. Hydrology Research, https://doi.org/10.2166/nh.2025.116" updated two "goodness-of-fit" metrics Revised R-squared (RRS) and Model Skill Score (MSC). These metrics allow the modeller to diagnostically identify and expose systematic issues behind model optimizations based on other ‘goodness-of-fits’ such as mean squared error. Here, the MATLAB codes for computing the updated "goodness-of-fit" metrics RRS and MSC are provided.

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Keywords

distance correlation, hydrological models, model performance evaluation, Nash–Sutcliffe efficiency, revised R-squared (RRS), R-squared

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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