Year: 2026
Type: article
Abstract: Hydropower is pivotal to the global transition toward carbon‐neutral energy, yet its actual potential remains constrained by uncertainties. Global assessments have traditionally relied on static metrics, such as dam height, which obscure the dynamic water fluctuations that govern operational reliability. Here, we leverage primary observations from the novel Surface Water and Ocean Topography (SWOT) satellite to construct the first global, observation‐based inventory of energy storage potential for 4,025 major reservoirs. We find that the global average hydraulic head was 32.13 ± 0.64 m in 2024, but with significant spatial heterogeneity shaped by topography and substantial intra‐annual variability. Fluctuations mostly exceed 10 m in monsoonal and arid regions, indicating greater variability in the head‐related component of hydropower storage potential. By generalizing these observations to the world's reservoirs (totally 26,388, >1 km 2 ), we quantify the global energy storage potential at 638.14 ± 218.52 TWh. Crucially, we identify a latent opportunity in non‐powered dams: retrofitting existing structures could unlock an additional gross theoretical energy storage potential of 84.88 ± 81.90 TWh, equivalent to 15.34% of current storage in powered dams, without considering engineering and operational constraints. By accumulating global reservoir energy storage potential based on commissioning dates and present‐day attributes, our analysis further reveals that this potential has expanded eightfold since 1960, with development shifting decisively from industrialized nations to developing regions. This satellite‐based assessment provides quantitative information on reservoir energy storage dynamics that can inform global energy‐system modeling, water‐energy planning, and evaluations of hydropower's potential contribution to decarbonization.
Source: Earth s Future
DOI: 10.1029/2026ef008836
Authors: Lin Huang, Chunqiao Song, Kai Liu, Pengfei Zhan, Xiaomei Fan, Hui Zhang, Yiguang Zou, Yaling Lin, Fanxuan Zeng, Jida Wang
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,180
Awards: G2249153570, G2332430696, G8915030263
OpenAlex ID: W7204910629
