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The KGE's component scores (Figure 3.) highlight that much of the lower KGE skill comes from the often high and mainly positive bias, and also larger variability errors. The correlation is more homogeneous, even though many of the low KGE areas also show low correlation, with exceptions, such as the upstream part of the Niger river basin, or some catchments in the Nile basin, which show high correlation but at the same time really high positive bias and some larger variability errors.
Figure 3. Bias and variability ratio and Pearson correlation of the GloFAS v4 simulation.
The timing error shows quite a lot of areal variability. Some of this probably comes from the potentially short sample period, which makes the verification scores less robust. Still, some pattern emerges and generally the errors are more negative than negative, i.e. the GloFAS v4.0 river discharge simulation is too early in the signal, so peaks happen earlier than in the observations.
Figure 4. Timing error of the GloFAS v4 simulation.
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