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On this page, the model performance is analysed over the final v4.0 reanalysis time series (https://cds.climate.copernicus.eu/cdsapp#!/dataset/cems-glofas-historical?tab=overview; which is not expected to be noticeably different to the one used in the calibration evaluation). In addition, all stations are considered hereDetails on methodologies of the station selection and other aspects of the verification, including the used metrics, are available on the verification methodology page (place holder GloFAS hydrological performance verification methodology).
Observation availability
All stations are considered in this general analysis, which have at least 1 year of good enough quality observation data in the 1979-2021 period (while it was at least 4 year years for the calibration), supplemented also with a separate station network without larger noticeable impact of reservoirs or lakes. In total, 2293 stations were considered for the general v4.0 verification with all stations (Figuyre 1, left column), 996 for the v4.0 vs v3.1 model comparison with stations used in calibration for both models both calibrations (Figure 1, middle column) and also a third set with 233 stations that were not used in either calibrations . Details on the station selection and other aspects of the verification, including the used metrics, are available on the verification methodology page (place holder GloFAS hydrological performance verification methodology).
General v4.0 performance
OBS availability
For this comparison, we used all stations with good quality river discharge observations and minimal human or lake influence that could be mapped (find the corresponding model river network location) onto the higher resolution v4.0 river network. In total 1987 stations could be considered as shown below with the available observation length (gaps are removed to compute the length).
(Figure 1, 3rd right column).
Figure 1. Number of years of available river discharge observations in the 1979-2021 reanalysis period with the full station list, the calibration station list and the non-calibration station list.
General v4.0 performance
KGE
The generic GloFAS v4.0 model performance is measured by the modified Kling Gupta efficiency (KGE) in Figure 2. High skill (above 0.7) is shown over much of the higher latitude areas and also some southest Asian and central south American areas. The lowest KGE, including even some catchments with no skill at all (below -0.41), are mainly spread across some tropical areas, often in central southern USA and Mexico and some areas in Africa, often in the drier climate.
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The KGE's component scores (Figure 3-4-5.) highlight that much of the lower KGE skill comes from the often high and mainly positive bias, and also larger variability errors. The bias ratio is over 1 for a lot of catchments in the tropical belt (please note, in this version of bias 0 is the optimal value), which means the simulation average is more than double the observation average value (i.e. twice as high as it should be). On the other hand, the variability error tend to be negatively oriented and many tropical catchment sees see too low variability in the simulations, often 1/3 less than in the observations (-0.33 to -0.5) or even at least 50% less than it should be according to the observations (darkest red).
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The timing error shows quite a lot of areal variability (Figure 6). Some of this probably comes from the potentially short sample period, which makes the verification scores less robust. Also, some larger errors in large variability areas can come from the type of catchments which have lower quality simulation, combined with less clear signal distribution, i.e. no clear peak and /trough structure, which can result in not no or little correlation change by shifting time-lagging the simulation.
Still, some pattern emerges and generally the errors are more negative than positive, i.e. the GloFAS v4.0 river discharge simulation is too early in the signal, so peaks happen earlier than in the observations. This is the case in many of the catchments in the higher latitudes, in Amazonia or in Australia. In terms of magnitude, the larger errors mean 5-10 days or even over 10 days timing problem.
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Figure 10. Correlation error difference maps between GloFAS v4.0 and v3.1 simulations (top row) and cumulative distributions of correlation for both v4.0 and v3.1 (bottom row). Using all all points (1st column), using only calibration points for both models without larger reservoir or lake influence (2nd column) and non-calibration points for both models without larger reservoir or lake influence (3rd column).
Timing
The correl
