Robust Hydropower Planning Balances Energy Generation, Carbon Emissions and Sediment Connectivity in the Mekong River Basin

We present a framework for strategic dam planning under uncertainty, which includes GHG emissions mitigation as a novel objective. We focus on the Mekong River Basin, a fast-developing region heavily relying on river-derived ecosystem services. We employ a multi-objective evolutionary algorithm to identify strategic dam portfolios for different hydropower expansion targets, using process-related and statistical models to derive indicators of sediment supply disruption and GHG emissions. We introduce a robust optimization approach that explores variations in optimal portfolio compositions for more than 5,000 state-of-the-world configurations, regarding sediment origins and trapping and GHG emissions. Thus, we can rank dam projects' attractiveness based on their frequency of inclusion in optimal portfolios and explore how uncertainty affects these rankings. Our results suggest that developing dams in the upper Mekong would be a more robust option for near-term development than, for example, the lower Mekong and its tributaries, for both environmental and energy objectives. Our work presents a novel approach to better understand the basin-scale cumulative impacts of dam development in high-uncertainty, data-scarce contexts like the Mekong Basin.