New research has been published that details a new computational approach for evaluating basin-level tradeoffs between hydropower and ecosystem services, with the goal of guiding sustainable dam siting in the Amazon.
The research - Reducing adverse impacts of Amazon hydropower expansion – was recently published in Science journal. As part of the research, an interdisciplinary team of environmental and computational experts developed ‘Amazon EcoVistas’, a novel framework to analyze proposed dam projects collectively – both for their energy generation, as well as their impacts on the environment. They analyzed five environmental criteria: river flow, river connectivity, sediment transport, fish biodiversity, and greenhouse gas emissions. The research says their tool uses artificial intelligence and high-performance computing to identify hydroelectric dam portfolios that meet energy production goals with the least environmental harm.
Locations and energy generation capacities of the 158 existing (red) and 351proposed (yellow) hydropower dams in the Amazon basin (Flecker et al. 2022).
Coauthor Stephen Hamilton, an ecosystem ecologist at Cary Institute of Ecosystem Studies, explains: “Continued hydropower development in the Amazon is inevitable. So how can that proceed in a way that optimizes energy output at the lowest environmental cost? The answer comes in selecting projects strategically, taking into account multiple environmental criteria that have thus far been too difficult to account for simultaneously in planning large numbers of potential projects.”
“Our tool allows us to evaluate hydroelectric projects for their collective impacts to nature and people on the scale of the entire watershed – a rare, yet critical approach, since the Amazon River and its tributaries flow through multiple countries with diverse topography,” adds coauthor Rafael Almeida, a former visiting graduate student at Cary who is currently an Assistant Professor at the University of Texas, Rio Grande Valley. The tool can also screen out particularly harmful projects, with Almeida adding: “Fragmentation of river systems, blockage of fish migrations, trapping of sediment, and emission of methane are all worsened by the absence of basin-wide planning.”
Running the ‘Amazon EcoVistas’ algorithm on the 158 existing and 351 proposed dams created scenarios based on all possible combinations of these projects. This allows it to determine the ‘Pareto-optimal frontier’ – or combination of hydropower projects that minimizes negative environmental effects for any given level of aggregate hydropower output. This process is extremely computationally intensive; between the 509 total projects, there are 2509 (or ~10153) possible combinations of projects – with six dimensions (energy output + the five environmental criteria) evaluated for each.
Lead author Alexander Flecker, Professor in the Department of Ecology and Evolutionary Biology at Cornell University, said: “All decisions around dam siting involve complex tradeoffs. The Pareto-optimal frontier provides a clear way to evaluate those tradeoffs as we seek to balance energy production and diverse environmental consequences.
“There’s no one-size-fits-all solution to minimize negative environmental impacts of dam construction. But the most damaging impacts can be averted by weighing the various ecological and social costs of different combinations of projects. Our novel computational framework is the first to make this kind of evaluation possible on such a vast basin-wide scale.”
The authors suggest that by identifying opportunities for more sustainable hydropower development, ‘Amazon EcoVistas’ could prove useful to energy planners, decision makers, and researchers working to implement strategic, whole-basin dam planning. It could also help evaluate priorities for dam removal in regions with aging dams such as North America and Europe, they said.