Articles | Volume 26, issue 13
https://doi.org/10.5194/hess-26-3537-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3537-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL)
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada
Hongren Shen
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada
Bryan A. Tolson
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada
Étienne Gaborit
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
Richard Arsenault
Department of Construction Engineering, École de technologie supérieure, Montreal, QC, Canada
James R. Craig
Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON, Canada
Vincent Fortin
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
Lauren M. Fry
Great Lakes Environmental Research Laboratory, National Oceanic and Atmospheric Administration, Ann Arbor, MI, USA
Martin Gauch
Institute for Machine Learning, Johannes Kepler University, Linz, Austria
Daniel Klotz
Institute for Machine Learning, Johannes Kepler University, Linz, Austria
Frederik Kratzert
Institute for Machine Learning, Johannes Kepler University, Linz, Austria
Google Research, Vienna, Austria
Nicole O'Brien
National Hydrological Service, Environment and Climate Change Canada, Burlington, ON, Canada
Daniel G. Princz
National Hydrological Service, Environment and Climate Change Canada, Saskatoon, SK, Canada
Sinan Rasiya Koya
Department of Civil and Environmental Engineering, University of Nebraska–Lincoln, Lincoln, NE, USA
Tirthankar Roy
Department of Civil and Environmental Engineering, University of Nebraska–Lincoln, Lincoln, NE, USA
Frank Seglenieks
National Hydrological Service, Environment and Climate Change Canada, Burlington, ON, Canada
Narayan K. Shrestha
National Hydrological Service, Environment and Climate Change Canada, Burlington, ON, Canada
André G. T. Temgoua
National Hydrological Service, Environment and Climate Change Canada, Burlington, ON, Canada
Vincent Vionnet
Meteorological Research Division, Environment and Climate Change Canada, Dorval, QC, Canada
Jonathan W. Waddell
Great Lakes Hydraulics and Hydrology Office, U.S. Army Corps of Engineers, Detroit, MI, USA
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Total article views: 7,642 (including HTML, PDF, and XML)
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Total article views: 1,869 (including HTML, PDF, and XML)
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Latest update: 16 Nov 2025
Executive editor
The study provides a unique effort undertaken by several research groups in the context of a remarkably instrumented large scale system. The latter is subject to a variety of measurement approaches and techniques and a wide range of models are considered in a remarkable inter-comparison study. Key methodological elements stemming from this very comprehensive work are highly relevant to the broad hydrological community.
The study provides a unique effort undertaken by several research groups in the context of a...
Short summary
Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Model intercomparison studies are carried out to test various models and compare the quality of...