Articles | Volume 21, issue 6
https://doi.org/10.5194/hess-21-2881-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-2881-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Global evaluation of runoff from 10 state-of-the-art hydrological models
Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
European Commission, Joint Research Centre (JRC), Via Enrico Fermi 2749, 21027 Ispra (VA), Italy
Albert I. J. M. van Dijk
Fenner School of Environment & Society, Australian National University (ANU), Canberra, Australia
Ad de Roo
European Commission, Joint Research Centre (JRC), Via Enrico Fermi 2749, 21027 Ispra (VA), Italy
Emanuel Dutra
European Centre for Medium-Range Weather Forecasts (ECMWF), Redding, UK
Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
Gabriel Fink
Center for Environmental Systems Research (CESR), University of Kassel, Kassel, Germany
Rene Orth
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Jaap Schellekens
Inland Water Systems Unit, Deltares, Delft, the Netherlands
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Saved (final revised paper)
Latest update: 28 May 2023
Short summary
Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
Runoff measurements for 966 catchments around the globe were used to assess the quality of the...