Reference number : GC-2017-Q1-01605, amendment number : , agreement type : G, recipient legal name : Craig, James (University of Waterloo), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Over the past fifty years, computational models of surface water and groundwater hydrology have become increasingly complex. Physically-based integrated hydrologic models with millions of nodes are now regularly deployed for flood forecasting and prediction, climate change investigation, and assessment of landscape sensitivity to changes in land use, land cover, management practices, or climate. These models are used to support critical management decisions about infrastructure, environmental practices, forestry, floodplain delineation, and land management in Canada and abroad. While prolific, these models still suffer from critical drawbacks in their ability to represent some common Canadian landscapes and phenomena, such as the wetlands in the Boreal plains of Alberta, thawing of permafrost hydrology in the Northwest Territories, and groundwater-surface water interactions in agricultural Ontario. The common impediment is our inability to map our process understanding generated through small-scale field studies to understanding of the larger phenomena occurring at the watershed scale, particularly when lateral water movement is a controlling factor. We are hampered by both our inability to measure critical quantities in the field for use in hydrologic models and by our limited understanding about how to algorithmically describe physical phenomena at scales of interest, especially with the presence of limited subsurface data. Many existing models can be fit to observations of streamflow, but often for the wrong reasons. 
 
The proposed research program focuses on the development of improved computational hydrology models to be used in support of water and energy resource management. The program links several ongoing and forthcoming projects aimed at improving our ability to model, understand, and predict the bulk behavior of watersheds while recognizing the limited availability of data. The primary objectives are to: (1) confront the critical issue of scale-dependence of physical processes in hydrologic models, using high-resolution models to identify controls on emergent watershed bulk behaviour; and (2) create, test, and apply novel, cost-efficient, and robust methods for simulating hydrologic phenomena at relevant scales for practical application. Advanced methods of model evaluation will be developed and used to test for and demonstrate improved model performance. By better depicting the physical phenomenon occurring in our watersheds at appropriate scales, these models and methods will advance our ability to manage Canada&rsquo;s water and energy resources., program purpose french : Over the past fifty years, computational models of surface water and groundwater hydrology have become increasingly complex. Physically-based integrated hydrologic models with millions of nodes are now regularly deployed for flood forecasting and prediction, climate change investigation, and assessment of landscape sensitivity to changes in land use, land cover, management practices, or climate. These models are used to support critical management decisions about infrastructure, environmental practices, forestry, floodplain delineation, and land management in Canada and abroad. While prolific, these models still suffer from critical drawbacks in their ability to represent some common Canadian landscapes and phenomena, such as the wetlands in the Boreal plains of Alberta, thawing of permafrost hydrology in the Northwest Territories, and groundwater-surface water interactions in agricultural Ontario. The common impediment is our inability to map our process understanding generated through small-scale field studies to understanding of the larger phenomena occurring at the watershed scale, particularly when lateral water movement is a controlling factor. We are hampered by both our inability to measure critical quantities in the field for use in hydrologic models and by our limited understanding about how to algorithmically describe physical phenomena at scales of interest, especially with the presence of limited subsurface data. Many existing models can be fit to observations of streamflow, but often for the wrong reasons. 
 
The proposed research program focuses on the development of improved computational hydrology models to be used in support of water and energy resource management. The program links several ongoing and forthcoming projects aimed at improving our ability to model, understand, and predict the bulk behavior of watersheds while recognizing the limited availability of data. The primary objectives are to: (1) confront the critical issue of scale-dependence of physical processes in hydrologic models, using high-resolution models to identify controls on emergent watershed bulk behaviour; and (2) create, test, and apply novel, cost-efficient, and robust methods for simulating hydrologic phenomena at relevant scales for practical application. Advanced methods of model evaluation will be developed and used to test for and demonstrate improved model performance. By better depicting the physical phenomenon occurring in our watersheds at appropriate scales, these models and methods will advance our ability to manage Canada&rsquo;s water and energy resources., agreement title english : Scale issues in connected landscapes: Resolving emergent behaviour for improved hydrologic modelling, agreement title french : Scale issues in connected landscapes: Resolving emergent behaviour for improved hydrologic modelling, agreement number : RGPIN, agreement value : 170000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada