The Greater Mekong Subregion is a transnational area bound together by the Mekong River basin and its immense hydropower resources, historically seen as the backbone of regional economic development. The basin is now punctuated by several dams, successful in attracting both international investors and fierce criticisms for their environmental and societal impacts. Surprisingly, no attention has been paid so far to the actual performance of these infrastructures: is hydropower supply robust with respect to the hydro-climatic variability characterizing Southeast Asia? When water availability is altered, what are the implications for power production costs and CO2 emissions? To answer these questions, we focus on the Laotian–Thai grid—the first international power trade infrastructure developed in the region—and use a power system model driven by a spatially-distributed hydrological-water management model. Simulation results over a 30-year period show that production costs and carbon footprint are significantly affected by droughts, which reduce hydropower availability and increase reliance on thermoelectric resources. Regional droughts across the Mekong basin are of particular concern, as they reduce the export of cheap hydropower from Laos to Thailand. To put the analysis into a broader climate-water-energy context, we show that the El Niño Southern Oscillation modulates not only the summer monsoon, but also the power system behaviour, shaping the relationship between hydro-climatological conditions, power production costs, and CO2 emissions. Overall, our results and models provide a knowledge basis for informing robust management strategies at the water-energy scale and designing more sustainable power plans in the Greater Mekong Subregion.

The hydropower fleet built in the Upper Mekong River, or Lancang, currently consists of eleven mainstream dams that can control about 55% of the annual flow to Northern Thailand and Laos. The operations of this fleet have become a source of controversy between China and downstream countries, with these dams often considered the culprit for droughts and other externalities. Assessing their actual impact is a challenging task because of the chronic lack of data on reservoir storage and operations. To overcome this challenge, we focus on the ten largest reservoirs and leverage satellite observations to infer 13-year time series of monthly storage variations. Specifically, we use area-storage curves (derived from a Digital Elevation Model) and time series of water surface area, which we estimate from Landsat images through a novel algorithm that removes the effects of clouds and other disturbances. We also use satellite radar altimetry data (Jason) to validate the results obtained from satellite imagery. Our results describe the evolution of the hydropower system and highlight the pivotal role played by Xiaowan and Nuozhadu reservoirs, which make up to ~85% of the total system’s storage in the Lancang River Basin. We show that these two reservoirs were filled in only two years, and that their operations did not change in response to the drought that occurred in the region in 2019-2020. Deciphering these operating strategies could help enrich existing monitoring tools and hydrological models, thereby supporting riparian countries in the design of more cooperative water-energy policies.