Greenhouse gas emissions from Hydropower: Challenges and Opportunities review

Hydropower is a renewable energy source critical for balancing the electricity grid and integrating variable wind and solar energy. However, its clean energy credentials are increasingly scrutinised due to its potential greenhouse gas (GHG) emissions, particularly methane—a potent GHG. While some reservoirs act as carbon sinks, others are significant emission sources. Accurately quantifying and addressing these emissions is essential to ensure hydropower’s role as a low-carbon energy source and to mitigate the climate-finance risks associated with reservoir emissions.

This paper critically analyzes existing methodologies for estimating hydropower-related GHG emissions, including direct field measurements, empirical and machine learning (ML) models, and simplified emission factors. These methods vary in their strengths, limitations, and uncertainties, with emissions being highly site-specific and influenced by climatic conditions, reservoir characteristics, water quality, and operational practices.

The analysis highlights how ML and hybrid modeling approaches can improve accuracy, providing more dynamic and scalable predictions of GHG emissions. These advancements enable the identification of high-emission reservoirs and inform the development of targeted mitigation strategies.

By advancing the understanding of hydropower emissions, this research supports the sustainable integration of hydropower into the energy mix, ensuring it displaces fossil fuel generation while maintaining its low-carbon status. Additionally, it provides actionable insights for policymakers to design strategies that promote low-carbon hydropower development, aligning with broader climate objectives.