Hydropower supplies roughly a quarter of Europe's renewable electricity, a critical pillar of the continent's energy mix. Operators plan production around expected water inflows to reservoirs: how much rain and snowmelt will arrive, and when. Getting this right matters for daily scheduling, price forecasting, and long-term investment decisions.
Climate change is making those plans less reliable. Warming temperatures alter snowpack accumulation and the timing of spring melt. Shifting precipitation patterns change how much water reaches reservoirs and in which season. Historical records, the traditional basis for planning, no longer capture what lies ahead. A hydropower operator using 50 years of past data to model future inflows risks systematic errors if the climate has moved on.
The challenge is acute in snow-dominated catchments across Scandinavia, the Alps, and the Pyrenees, where earlier snowmelt and changing seasonal flows directly affect when water is available for generation.
[Hydropower reservoir in northern Scandinavia with seasonal water level variations. Source: Vattenfall/C3S]
How EO can help
The Copernicus Climate Change Service (C3S) provides two things hydropower operators need. First, climate projections under different emissions scenarios, drawn from ensembles of global and regional climate models, show how temperature, precipitation, and river flow are expected to change over coming decades. Second, seasonal hydrological forecasts offer predictions of water availability up to six months ahead, allowing operators to plan reservoir management for the coming season rather than relying on climatological averages.
C3S also provides the Pan-European Climate Database (PECD), which includes hydropower-specific variables such as reservoir inflows and generation potential, covering both historical periods and future projections. These datasets can be linked to local hydrological models, bridging the gap between large-scale climate data and the specific catchments that feed individual reservoirs.
The practical value: operators can stress-test their portfolios against plausible climate futures and adjust production planning, maintenance schedules, and investment strategies accordingly.
Example 1: Vattenfall and the Lule River (Sweden)
Vattenfall, one of Europe's largest energy producers, draws about 30% of its electricity from hydropower. The company needed to understand how climate change might alter water recharge to its reservoirs on the Lule River in northern Sweden, a drainage basin of some 25,000 square kilometres running from the Norwegian border to the Bay of Bothnia.
Working with Sweden's national meteorological institute SMHI, Vattenfall used hydrological model ensembles from the C3S SWICCA (Service for Water Indicators in Climate Change Adaptation) demonstrator project alongside local observations. The long daily records and multiple climate scenarios available through C3S made it possible to evaluate projections against Vattenfall's own local data.
The results pointed to a clear shift: higher river flows in autumn, winter, and early spring, followed by lower flows in summer, with an earlier peak from snowmelt. For a hydropower operator, this changes when water is available for generation and when reservoirs fill and draw down. Armed with these projections, Vattenfall can adjust its long-term production planning and investment decisions.
Example 2: Seasonal forecasting for reservoir management
Beyond long-term projections, C3S seasonal forecasts help operators plan months ahead. The Smart Climate Hydropower Tool, developed using C3S Climate Data Store seasonal forecasts combined with machine learning, performs seasonal predictions of accumulated inflow to hydropower reservoirs. Operators in snowmelt-dominated regions can use these forecasts to commit to reservoir drawdown in early winter, anticipating future inflows rather than waiting for them to arrive.
EDF, France's dominant hydropower producer, develops in-house forecasting systems for river discharge and reservoir inflows, drawing on similar climate data. The approach is relevant across Europe's hydropower fleet, from Scandinavia to the Alps to the Iberian Peninsula.
