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To show the effect, the calibration simulation (with the final calibrated parameters) and the reanalysis are compared at each of the 228 stations, against the same observations and over the same period: the observations and period used in the calibration. The difference in skill is measured as ΔKGE = KGE′(reanalysis) − KGE′(calibration):
| ΔKGE | Meaning | Stations |
|---|---|---|
| below −0.10 | reanalysis worse | 31 |
| −0.10 to −0.02 | reanalysis slightly worse | 14 |
| −0.02 to 0.02 | similar | 178 |
| 0.02 to 0.10 | reanalysis slightly better | 4 |
| above 0.10 | reanalysis better | 1 |
At most of these stations (178 of 228), both simulations perform about the same, which means the reservoirs have little effect at the station. At 45 stations, the reanalysis scores lower, at 31 of them by more than 0.10. The median KGE′ is 0.70 for the calibration run and 0.64 for the reanalysis. Where the reservoirs have a large effect, the reanalysis typically shows damped flood peaks and higher low flows than the observations from before the reservoirs were built. This lowers the variability ratio γ and, as a result, KGE′.
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