Assimilating Surface Water and Ocean Topography(SWOT) Satellite and observational data for improved streamflow information

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The terrestrial hydrological cycle in Canada involves a complex interplay of stored water (snowpack, glaciers, lakes, wetlands, soil moisture, groundwater, permafrost, and river channel storage) within basins that are linked by coupled energy and mass exchanges to generate basins streamflow and water vapour to the atmosphere. Socio-economic benefits to Canada's water dependent economy are intimately tied to the availability of river flow or water storage, be it through the ability to grow crops, produce hydropower, have access to drinking water, or to be safe from floods. Given our reliance on water, the impacts of changes to water availability have implications for national security and personal safety, economic prosperity, and environmental sustainability. In addition to the changes in the hydrological cycle, a changing climate manifests itself, in part, through extreme weather events such as prolonged periods of heat and cold, more frequent storms and severe winds, and significant changes to precipitation regimes. This reality requires a sustainable and cost-effective hydro-meteorological network and prediction system. The international Surface Water and Ocean Topography (SWOT) hydrology team has developed discharge algorithms for all SWOT-observed rivers, but at a lower accuracy than what is possible at an in-situ gauge and a SWOT a priori River Database (SWORD) was built to support the development of SWOT observations. A major outcome for the SWORD database is to provide fixed node locations, reach boundaries, and high-resolution reach centre lines and attached hydrologic variables (width, slope, etc.) as well as a consistent topological system for global rivers 30 m wide and greater. This research will build on, and ensure compatibility with, the SWORD operational satellite products being proposed within the exiting hydrometric network in Canada. This will including improved geospatial intelligence, improved routing, and improved process representations, for deployment to large river basins in Canada. The hydrological modelling framework is consistent with the geospatial products used in the SWORD database, allowing for interchange between the hydrology and routing models and the SWORD characterization for SWOT. The result will be datasets and model-agnostic workflows (e.g., jupyter notebooks) that can easily allow for assimilation studies at the SWOT resolution, and subsequently used in applications around the world. This proposal will seek to develop innovative techniques to apply SWOT data for water cycle prediction in Canada by developing a comprehensive approach to i) assimilate SWOT data for discharge estimation, and ii) build on the current MESH modelling and forecast systems to better predict river basin hydrology. This will result in a novel SWOT-assimilation strategy for forecasting and hydrological model improvements.