- Award ID(s):
- Publication Date:
- NSF-PAR ID:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Page Range or eLocation-ID:
- 11891 to 11898
- Sponsoring Org:
- National Science Foundation
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A Meta-Analysis of Environmental Tradeoffs of Hydropower Dams in the Sekong, Sesan, and Srepok (3S) Rivers of the Lower Mekong BasinIn Mekong riparian countries, hydropower development provides energy, but also threatens biodiversity, ecosystems, food security, and an unparalleled freshwater fishery. The Sekong, Sesan, and Srepok Rivers (3S Basin) are major tributaries to the Lower Mekong River (LMB), making up 10% of the Mekong watershed but supporting nearly 40% of the fish species of the LMB. Forty-five dams have been built, are under construction, or are planned in the 3S Basin. We completed a meta-analysis of aquatic and riparian environmental losses from current, planned, and proposed hydropower dams in the 3S and LMB using 46 papers and reports from the past three decades. Proposed mainstem Stung Treng and Sambor dams were not included in our analysis because Cambodia recently announced a moratorium on mainstem Mekong River dams. More than 50% of studies evaluated hydrologic change from dam development, 33% quantified sediment alteration, and 30% estimated fish production changes. Freshwater fish diversity, non-fish species, primary production, trophic ecology, and nutrient loading objectives were less commonly studied. We visualized human and environmental tradeoffs of 3S dams from the reviewed papers. Overall, Lower Sesan 2, the proposed Sekong Dam, and planned Lower Srepok 3A and Lower Sesan 3 have considerable environmental impacts. Tradeoff analysesmore »
Large river systems, particularly those shared by developing nations in the tropics, exemplify the interconnected and thorny challenges of achieving sustainability with respect to food, energy, and water ( 1 ). Numerous countries in South America, Africa, and Asia have committed to hydropower as a means to supply affordable energy with net-zero emissions by 2050 ( 2 ). The placement, size, and number of dams within each river basin network have enormous consequences for not only the ability to produce electricity ( 3 ) but also how they affect people whose livelihoods depend on the local river systems ( 4 ). On page 753 of this issue, Flecker et al. ( 5 ) present a way to assess a rich set of environmental parameters for an optimization analysis to efficiently sort through an enormous number of possible combinations for dam placements and help find the combination(s) that can achieve energy production targets while minimizing environmental costs in the Amazon basin.
Deep Learning Segmentation of Satellite Imagery Identifies Aquatic Vegetation Associated with Snail Intermediate Hosts of Schistosomiasis in Senegal, AfricaSchistosomiasis is a debilitating parasitic disease of poverty that affects more than 200 million people worldwide, mostly in sub-Saharan Africa, and is clearly associated with the construction of dams and water resource management infrastructure in tropical and subtropical areas. Changes to hydrology and salinity linked to water infrastructure development may create conditions favorable to the aquatic vegetation that is suitable habitat for the intermediate snail hosts of schistosome parasites. With thousands of small and large water reservoirs, irrigation canals, and dams developed or under construction in Africa, it is crucial to accurately assess the spatial distribution of high-risk environments that are habitat for freshwater snail intermediate hosts of schistosomiasis in rapidly changing ecosystems. Yet, standard techniques for monitoring snails are labor-intensive, time-consuming, and provide information limited to the small areas that can be manually sampled. Consequently, in low-income countries where schistosomiasis control is most needed, there are formidable challenges to identifying potential transmission hotspots for targeted medical and environmental interventions. In this study, we developed a new framework to map the spatial distribution of suitable snail habitat across large spatial scales in the Senegal River Basin by integrating satellite data, high-definition, low-cost drone imagery, and an artificial intelligence (AI)-powered computermore »
Tackling climate change and human development challenges will require major global investments in renewable energy systems, including possibly into large hydropower. Despite well-known impacts of hydropower dams, most renewable energy assessments neither account for externalities of hydropower nor evaluate possible strategic alternatives. Here we demonstrate how integrating energy systems modeling and strategic hydropower planning can resolve conflicts between renewable energy and dam impacts on rivers. We apply these tools to Myanmar, whose rivers are the last free-flowing rivers of Asia, and where business-as-usual (BAU) plans call for up to 40 GW of new hydropower. We present alternative energy futures that rely more on scalable wind and solar, and less on hydropower (6.7–10.3 GW) than the BAU. Reduced reliance on hydropower allows us to use river basin models to strategically design dam portfolios for minimized impact. Thus, our alternative futures result in greatly reduced impacts on rivers in terms of sediment trapping and habitat fragmentation, and result in lower system costs ($8.4 billion compared to $11.7 billion for the BAU). Our results highlight specific opportunities for Myanmar but also demonstrate global techno-ecological synergies between climate action, equitable human development and conservation of riparian ecosystems and livelihoods.
Despite efforts to understand the hydrologic impact of hydropower dams, their influence on downstream river temperatures has gone unnoticed in data limited regions. Using 30 years of Landsat thermal infrared observations (1988–2018), we identified a relationship between dry season water temperature cooling trends and dam development in the 3S Basin, a major tributary of the Mekong River. Within a year of the beginning of operations of major dams in the 3S River Basin, rapid decreases in annual average dry season river temperature were observed ranging between 0.7 ° C and 2 ° C. Furthermore,
in situwater temperature observations confirmed decreasing river temperature for two major dam development events. Evidence was found that the 3S outflow has been cooling the Mekong River downstream of the confluence, by as much as 0.8 ° C in recent years. Our findings are critically important for understanding how fish and aquatic ecosystems will behave in the future as more hydropower dams are built in the Mekong River Basin.