Streamflow forecast information is increasingly available to hydropower owners and operators to assist with real-time operations of hydropower projects; however, this forecast information is regularly used incorrectly, is misunderstood, or is under-utilized, especially in the case of streamflow ensembles. Streamflow ensembles are multiple forecast traces that provide an indication of potential forecast uncertainty (or certainty) at a range of time horizons, and they can inform the operational decision-making process resulting in increased generation, reduced spill, and reduced risk, among other benefits.
This study includes three main components: a literature review of the use of streamflow ensembles; industry level surveys and interviews to benchmark the current use of ensembles; and an interactive Roadmap to guide users through the many different components of developing, verifying, processing, and using ensemble data.
Though the use of streamflow ensembles in hydropower operations can be extremely complicated, there are many simpler approaches to using this information. This study and an associated Roadmap will guide a wide range of users through these approaches, encouraging improved forecast-based decision-making.
ensembles, forecasting, verification, pre-processing, post-processing, probabilistic, uncertainty, hydropower, reservoir, streamflow, optimization, data management, decision-making, roadmap