Assessment of future water endowments: establishing a robust foundation to study regional water, food, energy, and environment dynamics

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The security of freshwater supplies is a growing concern worldwide. The water stress has been considered as the largest global risk and the main reason for regional insecurity. In Canada, water contributes up to $200 billion annually to the national economy from petroleum and agricultural production alone that may be jeopardized by variable water resources due to climate change. Climate change and variability undermine water resource planning by changing its spatial and temporal patterns, and changes in glacial meltwater flow among others. The result will be conflicts for water among agriculture, ecosystems, settlements, industry, and energy production, affecting regional water, energy, and food security in some regions while providing potential opportunities for growth in other regions. For a long-term regional planning of water resources in the face of the evolving climate change impacts, accurate projections of the impacts of climate change is necessary for adaptive planning. ******Research towards understanding water supply deals with a major theme, that of climate uncertainty, due to both natural variability and global warming. Application of process-based eco-hydro(geo)logical models (EHGM) is among the best available means to examine these problems. Despite advances in smaller scale modelling, the dynamic simulation of water supply is limited at regional scales due to inadequate representation of key hydrologic features including (1) snow and glacier melt and runoff; (2) interaction between water, vegetation, and soil types in wet, dry, and cold hydrologic conditions; and (3) surface water-groundwater (SW-GW) interactions. Furthermore, uncertainties exist in these projections due to poor integration of both short-term high frequency (e.g. El Niño/ENSO) and long-term lower frequency (e.g. Pacific Decadal Oscillations-PDO) climatic oscillations in the climate and hydrologic projections. Especially, most climate models do not perform well at simulating the lower frequency oscillations (i.e. PDO), and therefore in water projection models.***This fundamental Discovery funded research will develop regional water predictive models that consider cumulative effects of natural features (e.g., glaciers, snow, soil, vegetation, SW-GW interaction); anthropogenic factors (e.g., dams, irrigation, industrial development); and climate change and variability scenarios under different spatial and temporal scales. The end result will be tools that provide improved water management and policy responses to challenges in water security in the water-food-energy-environment nexus. **