Towards a Canadian National River Water Quality-Modelling System: State of Science and Future Prospects
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abstract
Water quality is of significant concern and ultimately critical to every Canadian’s quality of life and security. Canada has diverse and vast landscapes and stressors that impact various waterbodies differentially, with influencing factors including contaminant and nutrient loads from human activity (mining effluent, wastewater, agricultural runoff, plastics), landscape change (wetland drainage, urbanization) and climate change (warming water temperatures, longer open water seasons, extreme hydrological events, intensifying wildfires). Canadian rivers are especially important to the overall biogeochemistry, hydrology, biodiversity, and ultimate health of aquatic and terrestrial ecosystems. While each of Canada’s provinces and territories has extensive river water quality (physical, chemical, biotic) data and monitoring programs, Environment and Climate Change Canada coordinates various national programs that contribute to the collection and consolidation of these data and conducts extensive research into the study and modelling of key river water quality processes. Despite program-specific efforts, there remains poor capacity to predict current and future conditions in monitored and unmonitored Canadian rivers, particularly remote or northern rivers, due to a myriad of factors including lack of coordination amongst groups and examination of areas in which modelling efforts might be integrated. Herein, we review and analyse the current state of data availability, process studies, and modelling systems for Canadian river water quality. Our synthesis reveals that specific physical processes (water temperature, ice formation, permafrost thaw, sediment dynamics), biogeochemical processes (dissolved oxygen, dissolved organic matter, nutrient cycling, metals/contaminants) and ecological/biological features (biota mass, functional indicators) are well understood, though complex, and are amenable to empirical or mechanistic modelling. Review of this information assists us in identifying opportunities and challenges for developing a national water quality modelling system (NWQMS), that would eventually include similar modelling activities for parallel processes in lakes and integrated watersheds. We identify needs for stronger coordination of monitoring programs in remote areas, recommend use of novel remote sensing technologies, and development of a flexible, iterative ‘process’ for integrated modelling to which stakeholders beyond government can contribute. Such a platform would support short and long-term predictive models of Canadian water quality and ecosystem health, inform effluent concentration limits, and be an early warning system for source waters.
