Unfolding the relationship between seasonal forecasts skill and value in
hydropower production: A global analysis
Abstract
The potential benefits of seasonal streamflow forecasts for the
hydropower sector have been evaluated for several basins across the
world, but with contrasting conclusions on expected hydropower
production and economic gains. This raises the prospect of a complex
relationship between reservoir characteristics, forecast skill and
value. Here, we unfold the nature of this relationship by studying time
series of simulated power production for 735 headwater dams worldwide.
The time series are generated by running a detailed dam model over the
period 1958-2000 with three operating schemes: basic control rules,
perfect forecast-informed, and realistic forecast-informed. The
realistic forecasts are issued by bespoke models, based on lagged global
and local hydroclimatic variables, predicting seasonal monthly dam
inflows. Results show that most dams (94%) could benefit from perfect
forecasts. Yet, the benefits for each dam vary greatly and are primarily
controlled by the time to fill and the ratio between reservoir depth and
hydraulic head. When realistic forecasts are adopted, 25% of dams
demonstrate improvements with respect to basic control rules. In this
case, the likelihood of observing improvements is controlled not only by
design characteristics but also by forecast skill. We conclude our
analysis by identifying two groups of dams of particular interest: dams
that fall in regions expressing strong forecast accuracy and have the
potential to reap benefits from forecast-informed operations, and dams
with strong potential to benefit from forecast-informed operations but
lack forecast accuracy. Overall, these results represent a first
qualitative step towards informing site-specific hydropower studies.