Open AccessCanada One Water: integrated groundwater-surface-water-climate modelling for climate change adaptation
Author(s) -
H A J Russell,
Simon Frey
Publication year - 2021
Language(s) - English
Resource type - Reports
DOI - 10.4095/329092
Subject(s) - watershed , climate model , environmental science , climate change , environmental resource management , groundwater , weather research and forecasting model , downscaling , water balance , hydrological modelling , water resources , surface water , hydrology (agriculture) , geography , meteorology , climatology , computer science , engineering , precipitation , geology , environmental engineering , ecology , oceanography , geotechnical engineering , machine learning , biology
Canada 1 Water is a 3-year governmental multi-department-private-sector-academic collaboration to model the groundwater-surface-water of Canada coupled with historic climate and climate scenario input. To address this challenge continental Canada has beenallocated to one of 6 large watershed basins of approximately two million km2. The model domains are based on natural watershed boundaries and include approximately 1 million km2 of the United States. In year one (2020-2021) data assembly and validation of some 20 datasets (layers) is the focus ofwork along with conceptual model development. To support analysis of the entire water balance the modelling framework consists of three distinct components and modelling software. Land Surface modelling with the Community Land Model will support information needed for both the regional climatemodelling using the Weather Research & Forecasting model (WRF), and input to HydroGeoSphere for groundwater-surface-water modelling. The inclusion of the transboundary watersheds will provide a first time assessment of water resources in this critical international domain. Modelling is alsobeing integrated with Remote Sensing datasets, notably the Gravity Recovery and Climate Experiment (GRACE). GRACE supports regional scale watershed analysis of total water flux. GRACE along with terrestrial time-series data will serve provide validation datasets for model results to ensure that thefinal project outputs are representative and reliable. The project has an active engagement and collaborative effort underway to try and maximize the long-term benefit of the framework. Much of the supporting model datasets will be published under open access licence to support broad usage andintegration.