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HESS | Articles | Volume 23, issue 6
Hydrol. Earth Syst. Sci., 23, 2601–2614, 2019
https://doi.org/10.5194/hess-23-2601-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 23, 2601–2614, 2019
https://doi.org/10.5194/hess-23-2601-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Jun 2019

Research article | 17 Jun 2019

On the choice of calibration metrics for “high-flow” estimation using hydrologic models

Naoki Mizukami et al.
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Addor, N., Newman, A., Mizukami, N., and Clark, M.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, https://doi.org/10.5065/D6G73C3Q, 2017a. a, b
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Berghuijs, W. R., Woods, R. A., Hutton, C. J., and Sivapalan, M.: Dominant flood generating mechanisms across the United States, Geophys. Res. Lett., 43, 4382–4390, https://doi.org/10.1002/2016GL068070, 2016. a
Bergström, S.: The HBV model, in: Compute Models of Watershed Hydrology, edited by: Singh, V., chap. The HBV mo, Water Resouces Publications, Highlands Ranch Co., 1995. a
Bourgin, F., Andréassian, V., Perrin, C., and Oudin, L.: Transferring global uncertainty estimates from gauged to ungauged catchments, Hydrol. Earth Syst. Sci., 19, 2535–2546, https://doi.org/10.5194/hess-19-2535-2015, 2015. a
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We find that Nash–Sutcliffe (NSE)-based model calibrations result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimation. The use of Kling–Gupta efficiency (KGE) results in annual peak flow estimates that are better than from NSE, with only a slight degradation in performance with respect to other related metrics.
We find that Nash–Sutcliffe (NSE)-based model calibrations result in poor reproduction of...
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