Articles | Volume 23, issue 6
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, Oldrich Rakovec, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, Hoshin V. Gupta, and Rohini Kumar

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Cited articles

Addor, N., Newman, A., Mizukami, N., and Clark, M.: The CAMELS data set: catchment attributes and meteorology for large-sample studies,, 2017a. a, b
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313,, 2017b. a
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,, 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,, 2015. a
Short summary
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.