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

Mizukami, Naoki; Rakovec, Oldrich; Newman, Andrew J.; Clark, Martyn P.; Wood, Andrew W.; Gupta, Hoshin V.; Kumar, Rohini

doi:https://doi.org/10.5194/hess-23-2601-2019

Articles | Volume 23, issue 6

https://doi.org/10.5194/hess-23-2601-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-23-2601-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

Data sets

The CAMELS data set: catchment attributes and meteorology for large-sample studies N. Addor, A. Newman, N. Mizukami, and M. Clark https://doi.org/10.5065/D6G73C3Q

A large-sample watershed-scale hydrometeorological dataset for the contiguous USA A. Newman, K. Sampson, M. Clark, A. R. Bock, R. Viger, and D. Blodgett https://doi.org/10.5065/D6MW2F4D

mesoscale Hydrologic Model (Version v5.8) L. Samaniego, R. Kumar, J. Mai, M. Zink, S. Thober, M. Cuntz, and S. Attinger https://doi.org/10.5281/zenodo.1069203

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.