Weather Variability to Strain China's and Brazil’s Hydropower Sectors

Hydropower will play an important role in global efforts to reach net-zero emissions by 2050. It can be deployed as a mature and reliable source of clean energy generation as well as a form of dispatchable clean energy storage that can help balance the grid as more intermittent energy assets like wind and solar come online. 

But a new Gro analysis, using the models in Gro’s Climate Risk Navigator for Infrastructure, shows that hydropower generation capacity in China and Brazil, two of the biggest generators of hydropower globally, will likely face more climate-related stressors, specifically related to future temperature and precipitation variability.

Currently, hydropower delivers about 18% of the world’s total power generation capacity, and almost 70% of the world’s hydropower generation capacity is concentrated in 10 countries (figure 1 below), including China, the US, Brazil, Canada, Russia, India, Norway, Japan, France, and Venezuela.

Framing the Risks  

In addition to understanding changes in future gross water supply — the likelihood of more annual precipitation or of longer or more prevalent drought — it is critically important to understand the future variability of both precipitation and temperature in order to assess the risk that climate change poses for hydropower assets.

Under each IPCC climate change scenario, rainfalls, snowmelts, and droughts are projected to be less predictable, increasing the uncertainty of hydropower generation and the risks associated with hydropower investments. 

While climate change is expected to increase total annual precipitation in hydropower-heavy regions across the Northern Hemisphere, that potential increase in available reservoir inflow supply does not necessarily translate into increased hydropower generation from existing assets, if the delivery of that supply is significantly more variable than the historical average.

The future performance of these assets is further complicated over the long run by changes in peak temperature and temperature variability. Between lower and higher warming scenarios, increases in peak temperature may affect energy system capital investment requirements by as much as 20%; and increases in temperature variability may affect annual electricity demand — and with it system and asset operational stress — by as much as 10%.

Location-based temperature and precipitation variability metrics, such as the Gro Climate Indicators Projections (GCIP) - Weather Variability by Temperature, are therefore important when assessing a new or existing hydropower asset’s climate change vulnerability, and thus a plant’s viability.

China’s and Brazil’s Hydroelectric Plants Face Heightened Risk   

To determine which countries face the greatest hydropower generation capacity risks due to climate change, we created a district-level heatmap (figure 2 below) of areas with high capacity of hydropower generation and high temperature, low precipitation, or high weather variability using Gro’s district-level hydropower generation capacity data and district-level IPCC climate projections data for various future climate change scenarios.

According to our analysis, under scenario SSP5-8.5 (the scenario most commonly used by many risk managers), China is expected to experience higher precipitation with higher variability through 2100 in districts that are important for hydropower generation, suggesting a greater potential for an inconsistent supply of water for its hydropower plants. Brazil, meanwhile, is likely to face a future of lower precipitation with higher variability (although milder variability increases than that of China), signaling a drier and less certain future in key hydropower-generation districts. 

In addition to addressing questions about existing hydropower plants and new projects through 2100, our weather variability data can be used to examine the need for diversification away from or toward hydropower. More broadly, with Gro's GCIP - Weather Variability by Temperature and our GCIP - Weather Variability by Precipitation, users can also look at how volatile daily maximum temperatures and precipitation are at the district level for a specific asset through 2100.

1. See, e.g., Tarroja et al. (2016).
2. See, e.g., Khan et al. (2021).