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GWF-IMPC: Integrated Modelling Program for Canada
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Dataset Title
Land Use & Cover from the Great Lakes Aquatic Habitat Framework (GLAHF)
Abstract
The Land use & cover from the Great Lakes Aquatic Habitat Framework (GLAHF) were downloaded from GLAHF website (
https://www.glahf.org/data/ ). Data was converted into the NetCDF format. Data are then made available to the project collaborators on a private GitHub. Researchers interested in finding more about the data can email Juliane Mai (University of Waterloo; juliane.mai@uwaterloo.ca)
Purpose
The Great Lakes Runoff Inter-comparison Project (GRIP) includes a wide range of lumped and distributed models that are used operationally and/or for research purposes across Canada and the United States. Participating models are Global Environmental Multi-scale (GEM- Hydro), Weather Research and Forecasting (WRF-Hydro), MEC-Surface & Hydrology (MESH), Variable Infiltration Capacity (VIC), WATFLOOD, HYdrological Predictions for the Environment (HYPE), Soil & Water Assessment Tool (SWAT) and Large Basin Runoff Model (LBRM) The project aims to run all these models over several regions in Canada with Great Lakes, focusing on Lake Erie and Lake St.Clair as the initial domain (GRIP-E). This project will also focus on identifying a standard, consistent dataset for model building that all participants in the inter-comparison project can access and then process to generate their model-specific required inputs.
This data set is collected for the project titled "Integrated Modelling Program for Canada (IMPC): Theme 1", which is a Pillar 3 project under the Global Water Futures Program funded by Canada First Research Excellence Fund.
Citations
Wang, L., Riseng, C. M., Mason, L. A., Wehrly, K. E., Rutherford, E. S., McKenna, J. E.,Castiglione, C., Johnson, L. B., Infante, D. M., Sowa, S., Robertson, M., Schaeffer, J., Khoury, M., Gaiot, J., Hollenhorst, T., Brooks, C., & Coscarelli M. (2015). Land Use & Cover from the Great Lakes Aquatic Habitat Framework (GLAHF). Waterloo, Canada: Canadian Cryospheric Information Network (CCIN).
http://dx.doi.org/10.1016/j.jglr.2015.03.017
Download Links and Instructions
Data has been made available to project collaborators on a private GitHub repository.
To obtain data, go and see, or email Juliane Mai.