Strategic Dam Planning Accounting for Greenhouse Gases Emissions and River Sediment Connectivity

Hydroelectricity figures still prominently in climate change mitigation plans, being considered as a scalable and low-carbon source of renewable energy. This assumption has been increasingly challenged, as recent findings show that a large amount greenhouse gases (GHGs) such as methane (CH4) and carbon dioxide (CO2) can be emitted from reservoirs of some hydropower plants. Those emissions can be a major externality of hydropower generation. In the last decade, strategic siting of dams with a system-scale perspective has been proposed to minimize dam impacts on e.g., fish, sediment transport, and more recently also for minimizing greenhouse gas emissions from hydropower dam portfolios. Yet, what remains little studied is how uncertainty in environmental metrics, often evaluated based on few data and conceptual models, and conflicts between these metrics might impact portfolio selection. Herein, we present a three-objective optimization framework, aiming to minimize GHG emissions of future dams in the Mekong basin, while maximizing sediment load reaching the delta and annual energy generation. We apply a robust optimization approach to study if portfolio selection based on central estimates for sediment and GHG emissions are robust to large uncertainty in GHG estimates. Our findings indicate that storage dams in the upper basin are preferable to lowland run-of-river projects for both sediment and GHG emissions, and that portfolio selection is mostly robust to uncertainty in emission estimates. Our results also highlight that energy density (i.e., generation per reservoir surface area) is a key predictor for whether a dam is included in a certain portfolio. Our approach for robust optimization of dam portfolios under data uncertainty and considering for multiple environmental objectives opens opportunities to find good trade-offs and resolve environmental and economic conflicts in poorly monitored river basins.