Pushing back the boundaries to automating the operational hydrological forecasts used in hydropower reservoir management.

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One of the main challenges in hydrology is producing accurate, reliable and valuable forecasts on multiple timescales regarding future discharge in streams and rivers. High-quality forecasts enable water resources managers to make important decisions regarding the operation of their systems. Minimizing the damage caused by flood events and increasing hydropower generation efficiency justify the effort deployed by the hydrological community in this regard. ******Over the past 20 years, a plethora of publications has tackled the issue and hydrological forecasts are quickly getting increasingly reliable. Despite this progress, there are still major roadblocks to overcome, especially when considering the gap that exists between the generation of good forecasts, which are often considered as the end product, and their use in an operational context. Furthermore, operational hydrologic forecasting systems usually include inputs from an experienced forecaster who adjusts the hydrological model's initial states according to his best judgement prior to the forecast. This human intervention generates inconsistencies in the analysis of past system performance and thus obfuscates the underlying statistical properties of hydrological forecasts. In other words, the performance measures are muddled by human intervention and, as the saying goes, “you can't improve what you don't measure”. ******Consequently, evaluating the value of hydrological forecasts in an operational setting is a daunting task. It follows, then, that automating the forecasting aspect would allow more in-depth analysis and permit targeted improvements when paired with a reservoir system simulator. This research program aims to fill that gap and eventually allow targeted improvements in the forecast-decision process. The main objectives are to:******+ Move towards automating the hydrological forecast-decision chain for reservoir operation; and***+ Improve our understanding of the interactions between hydrological forecasts and reservoir management decision-support systems.******The following specific objectives are proposed to advance the research program:******- Develop novel approaches to improve upon inflow forecasting methods based on an analysis of traditional methods in an operational context;***- Coordinate the integration of model state initialization within a multi-model forecasting loop;***- Implement and expand upon a hydropower system simulator using state-of-the-art water release optimization algorithms; and***- Explore and quantify the value contained in hydrological forecasts for operational use within the simulator.******This research program will provide insight into the value of hydrological forecasts in hydropower generation. Considering that over 380 TWh of hydroelectricity ($16 billion) are produced annually in Canada, any improvement to the status quo will result in substantial economic and environmental gains.