Reducing adverse impacts of Amazon hydropower expansion

Can restoring water and sediment fluxes across a mega-dam cascade alleviate a sinking river delta?

Hydropower, although an attractive renewable energy source, can alter the flux of water, sediments, and biota, producing detrimental impacts in downstream regions. The Mekong River illustrates the impacts of large dams and the limitations of conventional dam regulating strategies. Even under the most optimistic sluicing scenario, sediment load at the Mekong Delta could only recover to 62.3 ± 8.2 million tonnes (1 million tonnes = 109 kilograms), short of the (100 to 160)-million tonne historical level. Furthermore, unless retrofit to reroute sediments, the dams are doomed to continue trapping sediment for at least 170 years and thus starve downstream reaches of sediment, contributing to the impending disappearance of the Mekong Delta. Therefore, we explicitly challenge the widespread use of large dead storages-the portion of the reservoirs that cannot be emptied-in dam designs. Smaller dead storages can ease sediment starvation in downstream regions, thereby buffering against sinking deltas or relative sea level rises.

Enhancing physically-based hydrological modeling with an ensemble of machine-learning reservoir operation modules under heavy human regulation using easily accessible data

Dams and reservoirs have significantly altered river flow dynamics worldwide. Accurately representing reservoir operations in hydrological models is crucial yet challenging. Detailed reservoir operation data is often inaccessible, leading to relying on simplified reservoir operation modules in most hydrological models. To improve the capability of hydrological models to capture flow variability influenced by reservoirs, this study proposes a hybrid hydrological modeling framework, which combines a process-based hydrological model with a machine-learning-based reservoir operation module designed to simulate runoff under reservoir operations. The reservoir operation module employs an ensemble of three machine learning models: random forest, support vector machine, and AutoGluon. These models predict reservoir outflows using precipitation and temperature data as inputs. The Soil and Water Assessment Tool (SWAT) then integrates these outflow predictions to simulate runoff. To evaluate the performance of this hybrid approach, the Xijiang Basin within the Pearl River Basin, China, is used as a case study. The results highlight the superiority of the SWAT model coupled with machine learning-based reservoir operation models compared to alternative modeling approaches. This hybrid model effectively captures peak flows and dry period runoff. The Nash-Sutcliffe Efficiency (NSE) in daily runoff simulations shows substantial improvement, ranging from 0.141 to 0.780, with corresponding enhancements in the coefficient of determination (R2) by 0.098-0.397 when compared to the original reservoir operation modules in SWAT. In comparison to parameterization techniques lacking a dedicated reservoir module, NSE enhancements range from 0.068 to 0.537, and R2 improvements range from 0.027 to 0.139. The proposed hybrid modeling approach effectively characterizes the impact of reservoir operations on river flow dynamics, leading to enhanced accuracy in runoff simulation. These findings offer valuable insights for hydrological forecasting and water resources management in regions influenced by reservoir operations.

Avoiding ecosystem and social impacts of hydropower, wind, and solar in Southern Africa's low-carbon electricity system

The scale at which low-carbon electricity will need to be deployed to meet economic growth, electrification, and climate goals in Africa is unprecedented, yet the potential land use and freshwater impacts from this massive build-out of energy infrastructure is poorly understood. In this study, we characterize low-impact onshore wind, solar photovoltaics, and hydropower potential in Southern Africa and identify the cost-optimal mix of electricity generation technologies under different sets of socio-environmental land use and freshwater constraints and carbon targets. We find substantial wind and solar potential after applying land use protections, but about 40% of planned or proposed hydropower projects face socio-environmental conflicts. Applying land and freshwater protections results in more wind, solar, and battery capacity and less hydropower capacity compared to scenarios without protections. While a carbon target favors hydropower, the amount of cost-competitively selected hydropower is at most 45% of planned or proposed hydropower capacity in any scenario-and is only 25% under socio-environmental protections. Achieving both carbon targets and socio-environmental protections results in system cost increases of 3-6%. In the absence of land and freshwater protections, environmental and social impacts from new hydropower development could be significant.

Emergy-based sustainability evaluation model of hydropower megaproject incorporating the social-economic-ecological losses

The sustainable development of the hydropower megaproject (HM) is one of the critical components of sustainable water resources management. Hence, an accurate assessment of the impacts of social-economic-ecological losses (SEEL) on the sustainability of the HM system is of utmost importance. This study proposes an emergy-based sustainability evaluation model incorporating the social-economic-ecological losses (ESM-SEEL), which integrated the inputs and outputs during HM's construction and operation into an emergy calculation account. The Three Gorges Project (TGP) on the Yangtze River is selected as a case study to comprehensively evaluate the HM's sustainability from 1993 to 2020. Subsequently, the emergy-based indicators of TGP are compared with several hydropower projects in China and worldwide to analyze the multi-impacts of hydropower development. The results showed that the river chemical potential (2.35 E+24sej) and the emergy losses (L) (1.39 E+24sej) are the primary emergy inflow sections (U) of the TGP system, accounting for 51.1% and 30.4% of the U, respectively. The flood control function of the TGP produced tremendous socio-economic benefits (1.24 E+24sej), accounting for 37.8% of the total emergy yield. The resettlement and compensation, water pollution during operation, fish biodiversity loss, and sediment deposition are the main L of the TGP, accounting for 77.8%, 8.4%, 5.6%, and 2.6%, respectively. Based on the enhanced emergy-based indicators, the assessment reveals that the sustainability level of the TGP falls in the middle range compared to other hydropower projects. Thus, along with maximizing the benefits of the HM system, it is necessary to minimize the SEEL of the HM system, which is a critical approach to promote the coordinated development of the hydropower and ecological environment in the Yangtze River basin. This study helps to understand the complex relationship between human and water systems and provides a novel framework that can be used as an evaluation index and insights for hydropower sustainability assessment.

Declining cost of renewables and climate change curb the need for African hydropower expansion

Across continental Africa, more than 300 new hydropower projects are under consideration to meet the future energy demand that is expected based on the growing population and increasing energy access. Yet large uncertainties associated with hydroclimatic and socioeconomic changes challenge hydropower planning. In this work, we show that only 40 to 68% of the candidate hydropower capacity in Africa is economically attractive. By analyzing the African energy systems' development from 2020 to 2050 for different scenarios of energy demand, land-use change, and climate impacts on water availability, we find that wind and solar outcompete hydropower by 2030. An additional 1.8 to 4% increase in annual continental investment ensures reliability against future hydroclimatic variability. However, cooperation between countries is needed to overcome the divergent spatial distribution of investment costs and potential energy deficits.

Scientific discovery in the age of artificial intelligence

Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment and accelerate research, helping scientists to generate hypotheses, design experiments, collect and interpret large datasets, and gain insights that might not have been possible using traditional scientific methods alone. Here we examine breakthroughs over the past decade that include self-supervised learning, which allows models to be trained on vast amounts of unlabelled data, and geometric deep learning, which leverages knowledge about the structure of scientific data to enhance model accuracy and efficiency. Generative AI methods can create designs, such as small-molecule drugs and proteins, by analysing diverse data modalities, including images and sequences. We discuss how these methods can help scientists throughout the scientific process and the central issues that remain despite such advances. Both developers and users of AI toolsneed a better understanding of when such approaches need improvement, and challenges posed by poor data quality and stewardship remain. These issues cut across scientific disciplines and require developing foundational algorithmic approaches that can contribute to scientific understanding or acquire it autonomously, making them critical areas of focus for AI innovation.

Sustainable irrigation and climate feedbacks

Agricultural irrigation induces greenhouse gas emissions directly from soils or indirectly through the use of energy or construction of dams and irrigation infrastructure, while climate change affects irrigation demand, water availability and the greenhouse gas intensity of irrigation energy. Here, we present a scoping review to elaborate on these irrigation-climate linkages by synthesizing knowledge across different fields, emphasizing the growing role climate change may have in driving future irrigation expansion and reinforcing some of the positive feedbacks. This Review underscores the urgent need to promote and adopt sustainable irrigation, especially in regions dominated by strong, positive feedbacks.

Large-scale hydropower impacts and adaptation strategies on rural communities in the Amazonian floodplain of the Madeira River

Understanding social and environmental impacts and household adaptation strategies in the face of expansions in energy infrastructure projects is essential to inform mitigation and interventions programs that promote well-being. Here we conducted surveys in seven communities distributed across varying degrees of proximity to a hydropower dam complex in the Brazilian Amazon along about 250 km of the floodplain of the Madeira River. Based on interviews with 154 fishers from these communities, we examine how fishers perceived changes in fisheries yields, changes in the composition of fish species, and whether and how adaptation strategies had evolved 8-9 years after the dams' construction. Most respondents (91%) indicated declines in yields after the dams for both upstream and downstream zones. Multivariate analyses revealed statistically significant differences in the composition of species yields in pre-and post-dam periods for all communities and in both upstream and downstream zones (p < 0.001). The composition of yields diversified after the dams, with an apparent decline in yields of species of greatest market value (e.g., catfishes Brachyplatystoma spp., Pseudoplatystoma spp., and jatuarana Brycon spp.), and increases in yields of a set of other smaller bodied and faster growing species (e.g., 'branquinhas' Psectrogaster spp., Potamohinna spp., and sardines Triportheus spp.). Both downstream and upstream fishers indicated that fishing profits decreased since the dams' construction (76.8% and 67.9%, respectively). To cope with these changes, the majority of both upstream and downstream fishers (>70%) stated they have had to devote more time to fishing after the dams were built. The time fishers spend traveling to fishing locations also increased for upstream communities (77.1%), but not for downstream communities. Thirty-four percent of the interviewees changed the gear they use to fish after the dams construction, with twice as many mentioning uses of non-selective gear, such as gillnets, and declining use of traditional fishing gears such as castnets and a trap ("covi"). Fish consumption overall decreased: fish was consumed 'everyday' before the dams, but 1-2 times per week or rarely after the dams were built. Although the species that declined were those of high economic value, 53% of fishers stated fish prices have increased overall after the dams. These results shed light on the potential challenges faced by fishers and which adaptation strategies they have evolved to maintain livelihoods since the construction of the dams.

Impacts of existing and planned hydropower dams on river fragmentation in the Balkan Region

The Balkan region has some of the best conserved rivers in Europe, but is also the location of ~3000 planned hydropower dams that are expected to help decarbonise energy production. A conflict between policies that promote renewable hydropower and those that prioritise river conservation has ensued, which can only be resolved with the help of reliable information. Using ground-truthed barrier data, we analysed the extent of current longitudinal river fragmentation in the Balkan region and simulated nine dam construction scenarios that varied depending on the number, location and size of the planned dams. Balkan rivers are currently fragmented by 83,017 barriers and have an average barrier density of 0.33 barriers/km after correcting for barrier underreporting; this is 2.2 times lower than the mean barrier density found across Europe and serves to highlight the relatively unfragmented nature of these rivers. However, our analysis shows that all simulated dam construction scenarios would result in a significant loss of connectivity compared to existing conditions. The largest loss of connectivity (-47 %), measured as reduction in barrier-free length, would occur if all planned dams were built, 20 % of which would impact on protected areas. The smallest loss of connectivity (-8 %) would result if only large dams (>10 MW) were built. In contrast, building only small dams (<10 MW) would cause a 45 % loss of connectivity while only contributing 32 % to future hydropower capacity. Hence, the construction of many small hydropower plants will cause a disproportionately large increase in fragmentation that will not be accompanied by a corresponding increase in hydropower. At present, hydropower development in the Balkan rivers does not require Strategic Environmental Assessment, and does not consider cumulative impacts. We encourage planners and policy makers to explicitly consider trade-offs between gains in hydropower and losses in river connectivity at the river basin scale.

Making thirsty cities sustainable: A nexus approach for water provisioning in Quito, Ecuador

In view of accelerated climate change and urban demographics, balancing human and ecosystem needs for water resources is a critical environmental challenge of global significance. Since water, agriculture, health, and energy are inextricably linked, sustainable development goals (SDGs) actions in one policy area commonly have impacts on the others, as well as on the ecosystems that natural resources and human activities ultimately depend upon. Managing urban water supply systems therefore requires a nexus approach that integrates goals across sectors, reduces the risk that SDG actions will undermine one another, and ensures sustainable resource use. We developed a transdisciplinary methodological framework based on a Pareto frontier analysis to define the sustainable solutions of a multi-objective optimization among four competing criteria, water provision, water quality, energy cost, and biodiversity conservation. The study was applied to three mountainous headwater basins in the Ecuadorian Andes, which provide around 30% of Quito's total water supply. We found that an optimized management of water intake structures would meet current consumption needs while reducing the probability of emergence of water pathogens and limiting the impact on aquatic biodiversity by 30% and 9% respectively, without any increase in energy costs for pumping water from other sources. Nonetheless, under future scenarios of climate change and water demand, higher energy consumption, and therefore an increase in operating costs, would be needed to meet urban demand and preserve environmental conditions. Overall, the range of Pareto optimal water supply strategies across the water-health-energy-biodiversity nexus provides valuable information for decision makers and offers support for achieving sustainable management of water resources.

Biodiversity underpins fisheries resilience to exploitation in the Amazon river basin

Inland fisheries feed greater than 150 million people globally, yet their status is rarely assessed due to their socio-ecological complexity and pervasive lack of data. Here, we leverage an unprecedented landings time series from the Amazon, Earth's largest river basin, together with theoretical food web models to examine (i) taxonomic and trait-based signatures of exploitation in inland fish landings and (ii) implications of changing biodiversity for fisheries resilience. In both landings time series and theory, we find that multi-species exploitation of diverse inland fisheries results in a hump-shaped landings evenness curve. Along this trajectory, abundant and large species are sequentially replaced with faster growing and smaller species. Further theoretical analysis indicates that harvests can be maintained for a period of time but that continued biodiversity depletion reduces the pool of compensating species and consequently diminishes fisheries resilience. Critically, higher fisheries biodiversity can delay fishery collapse. Although existing landings data provide an incomplete snapshot of long-term dynamics, our results suggest that multi-species exploitation is affecting freshwater biodiversity and eroding fisheries resilience in the Amazon. More broadly, we conclude that trends in landings evenness could characterize multi-species fisheries development and aid in assessing their sustainability.

Groundwater in Crisis? Addressing Groundwater Challenges in Michigan (USA) as a Template for the Great Lakes

Groundwater historically has been a critical but understudied, underfunded, and underappreciated natural resource, although recent challenges associated with both groundwater quantity and quality have raised its profile. This is particularly true in the Laurentian Great Lakes (LGL) region, where the rich abundance of surface water results in the perception of an unlimited water supply but limited attention on groundwater resources. As a consequence, groundwater management recommendations in the LGL have been severely constrained by our lack of information. To address this information gap, a virtual summit was held in June 2021 that included invited participants from local, state, and federal government entities, universities, non-governmental organizations, and private firms in the region. Both technical (e.g., hydrologists, geologists, ecologists) and policy experts were included, and participants were assigned to an agricultural, urban, or coastal wetland breakout group in advance, based on their expertise. The overall goals of this groundwater summit were fourfold: (1) inventory the key (grand) challenges facing groundwater in Michigan; (2) identify the knowledge gaps and scientific needs, as well as policy recommendations, associated with these challenges; (3) construct a set of conceptual models that elucidate these challenges; and (4) develop a list of (tractable) next steps that can be taken to address these challenges. Absent this type of information, the sustainability of this critical resource is imperiled.

Optimizing Amazonian dams for nature

Algorithms assess opportunities, forgone benefits, and environmental trade-offs.