Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)

Authors

• Juliane Mai, University of Waterloo
• Bryan A. Tolson, University of Waterloo
• Hongren Shen, University of Waterloo
• Etienne Gaborit, Environment and Climate Change Canada
• Vincent Fortin, Environment and Climate Change Canada
• Nicolas Gasset, Environment and Climate Change Canada
• Herve Awoye, University of Calgary
• Tricia A. Stadnyk, University of Calgary
• Lauren M. Fry, National Oceanic and Atmospheric
• Emily A. Bradley, Great Lakes Hydraulics and Hydrology Office
• Frank Seglenieks, Environment and Climate Change Canada
• Andre G.T. Temgoua, Environment and Climate Change Canada
• Daniel G. Princz, Environment and Climate Change Canada
• Shervan Gharari, University of Saskatchewan
• Amin Haghnegahdar, University of Saskatchewan
• Mohamed E. Elshamy, University of Saskatchewan
• Saman Razavi, University of Saskatchewan
• Martin Gauch, University of Waterloo
• Jimmy Lin, University of Waterloo
• Xiaojing Ni, US Environmental Protection Agency, Research Triangle Park
• Yongping Yuan, Office of Research and Development, US Environmental Protection Agency, Research Triangle Park
• Meghan McLeod, University of Waterloo
• Nandita B. Basu, University of Waterloo
• Rohini Kumar, Helmholtz Centre for Environmental Research–UFZ
• Oldrich Rakovec, Czech Univ. of Life Sciences
• Luis Samaniego, Helmholtz Centre for Environmental Research–UFZ
• Sabine Attinger, Helmholtz Centre for Environmental Research–UFZ
• Narayan K. Shrestha, University of Guelph
• Prasad Daggupati, University of Guelph
• Tirthankar Roy, University of Nebraska - LincolnFollow
• Sungwook Wi, University of Massachusetts Amherst
• Tim Hunter, , Great Lakes Environmental Research Laboratory, National Oceanic and Atmospheric Administration
• James R. Craig, University of Waterloo
• Alain Pietroniro, Environment and Climate Change Canada

Document Type

Article

Date of this Version

2021

Citation

J. Hydrol. Eng., 2021, 26(9): 05021020 : 10.1061/(ASCE)HE.1943-5584.0002097

Comments

OPEN ACCESS

Abstract

Hydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequence of the Great Lakes Runoff Intercomparison Projects. The densely populated Lake Erie watershed studied here is an important international lake that has experienced recent flooding and shoreline erosion alongside excessive nutrient loads that have contributed to lake eutrophication. Understanding the sources and pathways of flows is critical to solve the complex issues facing this watershed. Seventeen hydrologic and land-surface models of different complexity are set up over this domain using the same meteorological forcings, and their simulated streamflows at 46 calibration and seven independent validation stations are compared. Results show that: (1) the good performance of Machine Learning models during calibration decreases significantly in validation due to the limited amount of training data; (2) models calibrated at individual stations perform equally well in validation; and (3) most distributed models calibrated over the entire domain have problems in simulating urban areas but outperform the other models in validation.