Robust Dam Planning in the Mekong River Basin accounting for GHGs Emissions and River Sediment Connectivity
Abstract
Increasing hydropower production from large dams is considered an effective strategy to guarantee human development while tackling climate change, especially in developing countries with river basins whose hydropower potential is still mostly untapped. However, large dam development projects are known to have important negative repercussions on rivers and human livelihood, and can emit significant amounts of greenhouse gases from their reservoirs. While it has been shown that such negative externalities of dams are best mitigated through strategic impact/benefit assessments on a basin-scale, those assessments are hard to operationalize due to high uncertainty, and a lack of modeling tools.
In this work, we develop a framework for strategic dam planning under uncertainty. We use the Borg Multi-Objective Evolutionary Algorithm to solve a 3-objective optimization problem: maximize hydropower production and sediment supply to the river mouth, while minimizing GHGs emissions from reservoirs. The large-scale sediment connectivity model CASCADE is used to estimate sediment delivery, while GHGs emissions from dams are quantified via empirical formulas. To deal with large uncertainties and seek robust solutions, we perform an extensive Sensitivity Analysis on GHGs emissions, reservoir trapping efficiency, and catchment sediment yield. We apply this framework to the Mekong River basin, to determine Pareto-optimal dam portfolios. In our analysis, we identify some regions in the basin where, despite the vast uncertainties, dam development should be prioritized (e.g., the upstream Lancang River Basin) and others where it should be avoided (the downstream Tonle Sap Basin). Other areas, like the 3S Basin, are affected by high uncertainty and require further analysis to make robust recommendations. Our work presents a novel approach to better understand cumulative impacts of dam development at a basin scale in high uncertainty contexts, such as the Mekong River Basin.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFMGC22L0733T