Assessing the potential for gas supersaturation downstream of hydropower plants in Norway, Austria and Germany.

Hydroelectric power facilities can generate episodic total dissolved gas supersaturation (TDGS), which is harmful to aquatic life. We developed a decision tree-based risk assessment to identify the potential for TDGS at hydropower plants and conducted validation measurements at selected facilities. Applying the risk model to Norway's hydropower plants (n = 1696) identified 473 (28 %) high-risk plants characterized by secondary intakes and Francis or Kaplan turbines, which are prone to generating TDGS when air is entrained. More than half of them discharge directly to rivers (283, 17 % of total). Measurements of 11 high-risk plants showed that 8 of them exhibited biologically relevant TDGS (120 % to 229 %). In Austria and Germany, the analysis of hydropower plants was limited due to significant data constraints. Out of 153 hydropower plants in Austria, 80 % were categorized at moderate risk for TDGS. Two Austrian plants were monitored, revealing instances of TDGS in both (up to 125 %). In Germany, out of 403 hydropower plants, 265 (66 %) fell into the moderate risk, with none in the high-risk category. At a dam in the Rhine, TDGS up to 118 % were observed. Given the uncertainty due to limited data access and the prevalence of run-of-river plants in Austria and Germany, there remains an unclarified risk of TDGS generation in these countries, especially at spillways of dams and below aerated turbines. The results indicate a previously overlooked potential for the generation of biologically harmful TDGS at hydropower installations. It is recommended to systematically screen for TDGS at hydropower installations through risk assessment, monitoring, and, where needed, the implementation of mitigation measures. This is increasingly critical considering the expanding global initiatives in hydropower and efforts to maintain the ecological status of freshwater ecosystems.

Swing Trend Prediction of Main Guide Bearing in Hydropower Units Based on MFS-DCGNN.

Hydropower units are the core equipment of hydropower stations, and research on the fault prediction and health management of these units can help improve their safety, stability, and the level of reliable operation and can effectively reduce costs. Therefore, it is necessary to predict the swing trend of these units. Firstly, this study considers the influence of various factors, such as electrical, mechanical, and hydraulic swing factors, on the swing signal of the main guide bearing y-axis. Before swing trend prediction, the multi-index feature selection algorithm is used to obtain suitable state variables, and the low-dimensional effective feature subset is obtained using the Pearson correlation coefficient and distance correlation coefficient algorithms. Secondly, the dilated convolution graph neural network (DCGNN) algorithm, with a dilated convolution graph, is used to predict the swing trend of the main guide bearing. Existing GNN methods rely heavily on predefined graph structures for prediction. The DCGNN algorithm can solve the problem of spatial dependence between variables without defining the graph structure and provides the adjacency matrix of the graph learning layer simulation, avoiding the over-smoothing problem often seen in graph convolutional networks; furthermore, it effectively improves the prediction accuracy. The experimental results showed that, compared with the RNN-GRU, LSTNet, and TAP-LSTM algorithms, the MAEs of the DCGNN algorithm decreased by 6.05%, 6.32%, and 3.04%; the RMSEs decreased by 9.21%, 9.01%, and 2.83%; and the CORR values increased by 0.63%, 1.05%, and 0.37%, respectively. Thus, the prediction accuracy was effectively improved.

Water Scarcity Assessment of Hydropower Plants in China under Climate Change, Sectoral Competition, and Energy Expansion.

Hydropower plays a pivotal role in low-carbon electricity generation, yet many projects are situated in regions facing heightened water scarcity risks. This research devised a plant-level Hydropower Water Scarcity Index (HWSI), derived from the ratio of water demand for electricity generation to basin-scale available runoff water. We assessed the water scarcity of 1736 hydropower plants in China for the baseline year 2018 and projected into the future from 2025 to 2060. The results indicate a notable increase in hydropower generation facing moderate to severe water scarcity (HWSI >0.05), rising from 10% in 2018 to 24-34% of the national total (430-630 TWh), with a projected peak in the 2030s-2040s under the most pessimistic scenarios. Hotspots of risk are situated in the southwest and northern regions, primarily driven by decreased river basin runoff and intensified sectoral water use, rather than by hydropower demand expansion. Comparative analysis of four adaptation strategies revealed that sectoral water savings and enhancing power generation efficiency are the most effective, potentially mitigating a high of 16% of hydropower risks in China. This study provides insights for formulating region-specific adaptation strategies and assessing energy-water security in the face of evolving environmental and societal challenges.

Operational effects on aquatic carbon dioxide and methane emissions from the Belo Monte hydropower plant in the Xingu River, eastern Amazonia.

Operational demands and the natural inflow of water actively drive biweekly fluctuations in water levels in hydropower reservoirs. These daily to weekly fluctuations could have major effects on methane (CH4) and carbon dioxide (CO2) emissions via release of bubbles from reservoir bottom sediments (ebullition) or organic matter inputs, respectively. The impact of transient fluctuations in water levels on GHG emissions is poorly understood and particularly so in tropical run-of-the-river reservoirs. These reservoirs, characterized by high temperatures and availability of labile organic matter, are usually associated with extensive CH4 generation within bottom sediments. The aim of this study is to determine how water level fluctuations resulting from the operation of the Belo Monte hydropower plant on the Xingu River, eastern Amazon River Basin, affect local CO2 and CH4 emissions. Between February and December 2022, we monitored weekly fluxes and water concentrations of CO2 and CH4 in a site on the margin of the Xingu reservoir. Throughout the study period, fluxes of CO2 and CH4 were 118 ± 137 and 3.62 ± 8.47 mmol m-2 d-1 (average ± 1SD) while concentrations were 59 ± 29.77 and 0.30 ± 0.12 µM, respectively. The fluxes and water concentrations of CO2 were clearly correlated with the upstream discharge, and the variation observed was more closely associated with a seasonal pattern than with biweekly fluctuations in water level. However, CH4 fluxes were significantly correlated with biweekly water level fluctuations. The variations observed in CH4 fluxes occurred especially during the high-water season (February-April), when biweekly water level fluctuations were frequent and had higher amplitude, which increased CH4 ebullition. Reducing water level fluctuations during the high-water season could decrease ebullitive pulses and, consequently, total flux of CH4 (TFCH4) in the reservoir margins. This study underscores the critical role of water level fluctuations in near-shore CH4 emissions within tropical reservoirs and highlights significant temporal variability. However, additional research is necessary to understand how these findings can be applied across different spatial scales.

Improving flood and drought management in transboundary Upper Jhelum Basin-South Asia.

The two contrasting extremes of the hydrological spectrum have substantial and far-reaching impacts on a wide range of sectors including water resources, agriculture and food security, energy, infrastructure, and ecosystem. The compounding factors of climate change, burgeoning population, and rapid economic development create unprecedented challenges in devising effective and sustainable strategies to cope with these natural disasters and minimize their devastating impacts. This study identifies the geographical areas that are prone to meteorological wet-dry extreme events, as drivers of hydrologic floods and droughts, and their temporal compounding in the transboundary Upper Jhelum Basin-South Asia. Additionally, the study provides a comprehensive overview of the existing and proposed water development projects, their coping capacities, and potential impacts that may be positive or negative in hydrologic, social, economic and environment terms. Extensive review and data analysis revealed that the both Pakistan and India, along with state governments, have implemented a significant number of water-related projects across the basin, however significant progress towards achieving their stated goals remains elusive. Currently, Pakistan operates 15 runoff river type hydropower plants, and an additional 11 similar projects are under construction. In contrast, Indian administrative Kashmir has 10 such plants in operation and 4 under construction. The primary factors that impede the realization of expected benefits from these projects are geography, high flow variability across seasons, climate change, insufficient planning, geopolitical disputes, lack of transboundary cooperation, financial limitations, and reservoir operation. Based on these factors, the present study suggests some alternative water management measures that offer flexibility, cost-effectiveness, accessibility, and a low environmental impact. These solutions include implementation of sub-surface floodwater harvesting system in the southwest of the basin, where extreme wet and dry events occur in close succession, augmentation of existing hydropower reservoirs with floating photovoltaic technology, and non-structural measures, including early warning systems, ecosystems-based adaptation, and green infrastructure interventions such as restoring headwater forests, reclaiming floodplains, and wetlands. This will result in reduced flood and drought impacts at local and downstream areas and reduce the reliance of local communities on forest wood.

Temporal and spatial biosonar activity of the recently established uppermost Yangtze finless porpoise population downstream of the Gezhouba Dam: Correlation with hydropower cascade development, shipping, hydrological regime, and light intensity.

Numerous dams disrupt freshwater animals. The uppermost population of the critically endangered Yangtze finless porpoise has been newly formed below the Gezhouba Dam, however, information regarding the local porpoise is scarce. Passive acoustic monitoring was used to detect the behaviors of porpoises below the Gezhouba Dam. The influence of shipping, pandemic lockdown, hydrological regime, and light intensity on the biosonar activity of dolphins was also examined using Generalized linear models. Over the course of 4 years (2019-2022), approximately 848, 596, and 676 effective monitoring days were investigated at the three sites, from upstream to downstream. Observations revealed significant spatio-temporal biosonar activity. Proportion of days that are porpoise positive were 73%, 54%, and 61%, while porpoise buzz signals accounted for 78.49%, 62.35%, and 81.30% of all porpoise biosonar at the three stations. The biosonar activity of porpoises was much higher at the confluence area, particularly at the MZ site, during the absence of boat traffic, and during the Pandemic shutdown. Temporal trends of monthly, seasonal, and yearly variation were also visible, with the highest number of porpoises biosonar detected in the summer season and in 2020. Significant correlations also exist between the hydrological regime and light intensity and porpoise activity, with much higher detections during nighttime and full moon periods. Hydropower cascade development, establishment of a natural reserve, fish release initiatives, and implementation of fishing restrictions may facilitate the proliferation of the porpoise population downstream of the Gezhouba Dam within the Yichang section of the Yangtze River. Prioritizing restoration designs that match natural flow regimes, optimize boat traffic, and reduce noise pollution is crucial for promoting the conservation of the local porpoises.

Evolution and future prospects of hydropower sector in Nepal: A review.

Nepal is one of the pioneers of hydropower development among Asian countries. The plethora of fast-flowing rivers provides immense potential for hydropower generation. However, Nepal still lacks a clear blueprint for the overall development and management of this sector. This paper aims to review the evolution of hydropower development, future prospects and roadblocks to hydropower development. With the growing energy demands projected to reach as high as 41,264.82 Gigawatt hours (GWh) in 2030 and 115,294.4 GWh in 2040 under different scenarios, this paper highlights the huge prospects the sector holds. It also proposes a focus on storage-type hydropower plants and concepts of energy banking to address the incipient condition of seasonal energy mismatch in the country, which has developed a condition of energy shortage during the winter and energy surplus during the monsoon. Moreover, projected changes in hydro-climatic extremes under the climate change scenarios is likely to affect water availability and subsequently the energy production in the majority of hydropower projects. Thus, this review can serve as a guideline to help understand the current scenario and make rational decisions and policies for the future management of the hydropower sector of the country.

Existing levels of biodiversity and river location may determine changes from small hydropower developments.

Global ecosystems are facing anthropogenic threats that affect their ecological functions and biodiversity. However, we still lack an understanding of how biodiversity can mediate the responses of ecosystems or communities to human disturbance across spatial gradients. Here, we examined how existing, spatial patterns of biodiversity influence the ecological effects of small hydropower plants (SHPs) on macroinvertebrates in river ecosystems. This study found that levels of biodiversity (e.g., number of species) can influence the degrees of its alterations by SHPs occurring along elevational gradients. The results of the study reveal that the construction of SHPs has various effects on biodiversity. For example, low-altitude areas with low biodiversity (species richness less than 12) showed a small increase in biodiversity compared to high-altitude areas (species richness more than 12) under SHP disturbances. The increases in the effective habitat area of the river segment could be a driver of the enhanced biodiversity in response to SHP effects. Changes in the numerically dominant species contributed to the overall level of community variation from disturbances. Location-specific strategies may mitigate the effects of SHPs and perhaps other disturbances.

A CMIP6 multi-model based analysis of potential climate change effects on watershed runoff using SWAT model: A case study of kunhar river basin, Pakistan.

The hydrological regimes of watersheds might be drastically altered by climate change, a majority of Pakistan's watersheds are experiencing problems with water quality and quantity as a result precipitation changes and temperature, necessitating evaluation and alterations to management strategies. In this study, the regional water security in northern Pakistan is examined about anthropogenic climate change on runoff in the Kunhar River Basin (KRB), a typical river in northern Pakistan using Soil and Water Assessment tool (SWAT) and flow durarion curve (FDC). Nine general circulation models (GCMs) were successfully utilized following bias correction under two latest IPCC shared socioeconomic pathways (SSPs) emission scenarios. Correlation coefficients (R2), Nash-Sutcliffe efficiency coefficients (NSE), and the Percent Bias (PBIAS) are all above 0.75. The conclusions demonstrate that the SWAT model precisely simulates the runoff process in the KRB on monthly and daily timescales. For the two emission scenarios of SSP2-4.5 and SSP5-8.5, the mean annual precipitation is predicted to rise by 3.08 % and 5.86 %, respectively, compared to the 1980-2015 baseline. The forecasted rise in mean daily high temperatures is expected to range from 2.08 °C to 3.07 °C, while the anticipated increase in mean daily low temperatures is projected to fall within the range of 2.09 °C-3.39 °C, spanning the years 2020-2099. Under the two SSPs scenarios, annual runoff is estimated to increase by 5.47 % and 7.60 % due to climate change during the same period. Future socioeconomic growth will be supported by a sufficient water supply made possible by the rise in runoff. However, because of climate change, there is a greater possibility of flooding because of increases in both rainfall and runoff. As a result, flood control and development plans for KRB must consider the climate change's possible effects. There is a chance that the peak flow will move backwards relative to the baseline.

Optimizing hydropower scheduling through accurate power load prediction: A practical case study.

Hydropower stations that are part of the grid system frequently encounter challenges related to the uneven distribution of power generation and associated benefits, primarily stemming from delays in obtaining timely load data. This research addresses this issue by developing a scheduling model that combines power load prediction and dual-objective optimization. The practical application of this model is demonstrated in a real-case scenario, focusing on the Shatuo Hydropower Station in China. In contrast to current models, the suggested model can achieve optimal dispatch for grid-connected hydropower stations even when power load data is unavailable. Initially, the model assesses various prediction models for estimating power load and subsequently incorporates the predictions into the GA-NSGA-II algorithm, specifically an enhanced elite non-dominated sorting genetic algorithm. This integration is performed while considering the proposed objective functions to optimize the discharge flow of the hydropower station. The outcomes reveal that the CNN-GRU model, denoting Convolutional Neural Network-Gated Recursive Unit, exhibits the highest prediction accuracy, achieving R-squared and RMSE (i.e., Root Mean Square Error) values of 0.991 and 0.026, respectively. The variance between scheduling based on predicted load values and actual load values is minimal, staying within 5 (m3/s), showcasing practical effectiveness. The optimized scheduling outcomes in the real case study yield dual advantages, meeting both the demands of ship navigation and hydropower generation, thus achieving a harmonious balance between the two requirements. This approach addresses the real-world challenges associated with delayed load data collection and insufficient scheduling, offering an efficient solution for managing hydropower station scheduling to meet both power generation and navigation needs.

A design of a nature-like fishway to solve the fractured river connectivity caused by small hydropower based on hydrodynamics and fish behaviors.

Achieving a harmonious alignment between the biological characteristics of fish and hydrodynamics patterns is crucial for ensuring the efficacy of fish passage facilities. In this study, based on the hydrodynamic characteristics of the river and the biological characteristics of fish, we evaluated the internal flow field in the nature-like fishway of Congen II hydropower station located along the Chabao river and explored methods to improve the operation efficiency. Based on comprehensive considerations of the flow field, turbulent kinetic energy, and the migration pathways of fish, it is found that the implementation of a continuous oblique bottom slope represents a more cost-effective and operationally convenient solution. The influence of different permutation of bulkheads in the nature-like fishway on operational efficiency was further examined. Our investigation revealed that the nature-like fishway with the continuous slope of 2% and the arrangement of three bulkheads in each row (model 3) exhibited a relatively simple velocity distribution and linear flow line, which poses challenges for fish in locating resting areas. In addition, the distribution of low turbulence kinetic energy area in the mainstream made it less favorable for fish to transition from the mainstream to the rest area within the fishway. The nature-like fishway with the continuous slope of 2% and the arrangement of two or three bulkheads in staggered rows (model 4) demonstrated better performance. Several potential fish migration routes for both model 3 and model 4 were proposed based on the numerical simulation results. In model 3, fish exhibited a continuous sprint through the concentrated high-speed area, which was less favorable for fish to rest and forage. In contrast, model 4 exhibited a diversified flow velocity distribution, enabling fish to make timely changes in their direction during migration. This feather proved to be advantageous in enhancing fish migration within the passage. The design of nature-like fishway in this study provides an important reference and technical support for the construction and optimization of the nature-like fishway for low dams, and is of great significance for restoring river connectivity destroyed by small hydropower construction and improving fish migration.

Comparative analysis of hydro energy determinants for European Economies using Golden Cut-oriented Quantum Spherical fuzzy modelling and causality analysis.

This article presents a comparative analysis of the determinants of hydropower for European economies using Golden Cut oriented Quantum Spherical fuzzy modelling and causality analysis in 24 European countries over the period 2001-2020. The indicators chosen for the analysis are inflation, population, GDP per capita, CO2 and hydropower consumption. The analysis shows that the selected groups of countries are characterised by an inverse relationship between GDP per capita and hydropower consumption, suggesting a bi-directional causal relationship, which also confirms the novelty of this paper. Furthermore, another analysis is carried out using the fuzzy decision-making methodology. In this framework, the directions of influence of the five selected indicators are constructed: GDP per capita (criterion 1, D = 88.656, E = 88.083), hydropower consumption (criterion 2, D = 89.471, E = 88.677), population (criterion 3, D = 87.705, E = 89.228), CO2 emissions (criterion 4, D = 88.578, E = 89.186) and inflation (criterion 5, D = 88.943, E = 88.180). The Quantum Spherical fuzzy methodology is used for this purpose. The values of D and E are measures of the sum of the rows and columns of the overall relationship matrix. Hydropower consumption is the main criterion. It is understood that two different analyses give similar results, namely the bidirectional causal relationship between criteria 1 and 2.

Stability analysis of pumped storage hydropower plant in abandoned open-pit mine affected by dynamic surface subsidence of combined mining.

The construction of a pumped storage hydropower plant (PSHP) in an abandoned open-pit mine is a potential alternative to green mining and energy storage, which can increase the utilization rate of renewable energy and develop residual resources of abandoned mines. Dynamic surface subsidence affected by combined underground and open-pit mining (CUOPM) seriously affects the construction and operation of the PSHP and is one of the critical scientific issues that needs to be solved immediately. The stability of the PSHP was analyzed and treatment scheme of the goafs was proposed based on on-site measurement, theoretical analysis, and numerical simulation. First, the distribution of goafs in the Haizhou open-pit mining area was investigated and surface subsidence value was obtained using InSAR technology and ground monitoring. Secondly, the surface subsidence mechanism affected by CUOPM is analyzed and indicates the subsidence maximum values and scope of influence are greater than those of single underground mining. A dynamic surface subsidence prediction model for combined mining is established based on the Knothe time function model. Thirdly, based on the CVISC model, the numerical calculation models were established by using FLAC3D, and the characteristics and laws of surface subsidence in different periods of CUOPM were studied. The comparative analysis of the observation results shows that the proposed model and numerical simulation calculation method have excellent applicability and accuracy. Finally, a stability evaluation method of PSHP was established, and the results of the evaluation show that the affected areas are the semi-ground powerhouse (SGPH) and the west side of the lower reservoir. The method of grouting filling was used to treat the goafs, and the results showed that it effectively alleviates the dynamic surface subsidence affected by CUOPM, and provides a safety guarantee for PSHP.

Poverty-Food Insecurity Nexus in the Post-Construction Context of a Large Hydropower Dam in the Brazilian Amazon.

Within the 2030 Sustainable Development Agenda, large hydropower dams are positioned as a sustainable energy source, notwithstanding their adverse impacts on societies and ecosystems. This study contributed to ongoing discussions about the persistence of critical social issues, even after the investments of large amounts of resources in areas impacted by the construction of large hydropower dams. Our study focused on food insecurity and evaluated this issue in the city of Altamira in the Brazilian Amazon, which has been profoundly socially and economically impacted by the construction, between 2011 and 2015, of Brazil's second-largest dam, namely, Belo Monte. A survey in Altamira city featured a 500-household random sample. Structural equation modeling showed conditioning factors of 60% of the population experiencing varying food insecurity degrees. Poverty, female-led households, lower education, youth, and unemployment were strongly linked to higher food insecurity. Crowded, officially impacted, and resettled households also faced heightened food insecurity. Our findings underscore the food insecurity conditions in the region impacted by the Belo Monte dam, emphasizing the need to take into account this crucial issue while planning and implementing hydropower dams.

Recent Advances of Green Electricity Generation: Potential in Solar Interfacial Evaporation System.

Solar-driven interfacial evaporation (SDIE) has played a pivotal role in optimizing water-energy utilization, reducing conventional power costs, and mitigating environmental impacts. The increasing emphasis on the synergistic cogeneration of water and green electricity through SDIE is particularly noteworthy. However, there is a gap of existing reviews that have focused on the mechanistic understanding of green power from water-electricity cogeneration (WEC) systems, the structure-activity relationship between efficiency of green energy utilization in WEC and material design in SDIE. Particularly, it lacks a comprehensive discussion to address the challenges faced in these areas along with potential solutions. Therefore, this review aims to comprehensively assess the progress and future perspective of green electricity from WEC systems by investigating the potential expansion of SDIE. First, it provides a comprehensive overview about material rational design, thermal management, and water transportation tunnels in SDIE. Then, it summarizes diverse energy sources utilized in the SDIE process, including steaming generation, photovoltaics, salinity gradient effect, temperature gradient effect, and piezoelectric effect. Subsequently, it explores factors that affect generated green electricity efficiency in WEC. Finally, this review proposes challenges and possible solution in the development of WEC.

An electricity market-based approach to finance environmental flow restoration.

As environmental flow demands become better characterized, improved water allocation and reservoir operating solutions can be devised to meet them. However, significant economic trade-offs are still expected, especially in hydropower-dominated basins. This study explores the use of the electricity market as both an institutional arrangement and an alternative financing source to handle the costs of implementing environmental flows in river systems managed for hydropower benefits. A framework is proposed to identify hydropower plants with sustainable operation within the portfolio of power sources, including a cost-sharing mechanism based on the electricity market trading to manage a time-step compensation fund. The objective is to address a common limitation in the implementation of environmental flows by reducing the dependence on government funding and the necessity for new arrangements. Compensation amounts can vary depending on ecosystem restoration goals (level of flow regime restoration), hydrological conditions, and hydropower sites characteristics. The application in the Paraná River Basin, Brazil, shows basin-wide compensation requirements ranging from zero in favorable hydrological years to thousands of dollars per gigawatt-hour generated in others. Each electricity consumer's contribution to the compensation fund is determined by their share of energy consumption, resulting in values ranging from cents for residential users to thousands of dollars for industrial facilities. Finally, the compensation fund signals the economic value of externalities in energy production. For residential users, achieving varying levels of ecosystem restoration led to an electricity bill increase of less than 1 %. For larger companies, the increase ranged from less than 1 %-12 %.

Multi-purpose reservoir operation oncomitant with estimating hydropower potential using multifarious hydrological models.

The research aims at determining the optimal release rule to increase the capacity of Rib reservoir. The reservoir inflow using HBV-light hydrological model embracing optimal reservoir operation through HEC-ResSim model were used to prepare an optimum operational plan. The potential of the river for hydropower generation prioritise the demand at a specified level regarding storage capacity (m3), level of reservoir (m), and the relation between inflow and outflow of the reservoir. From the model performance features, the coefficient of correlation (R2) and Nash Sutcliffe Efficiency (NSE) were determined to be, respectively, 0.77 and 0.73 for calibration and 0.72 and 0.70 for validation. The Sobol approach was used for detailed sensitivity analysis of DROP model parameters based on the performance of C2M on outflows and volumes. The results suggest that the threshold coefficient characterizing the demand-controlled release level is the most significant parameter. According to the simulation's findings, the reservoir's average regulated release is calculated to be 22.86 m3/s, and its average monthly hydropower output is 6.73 MW. Average annual hydropower energy was estimated as 58.955 GW h/year and mean annual inflow of reservoir volume of water to be 223.54 Mm3. This volume of water is adequate to accommodate total annual irrigation demand, environmental obligation, and other respective requirements in the downstream. The demand for hydropower and irrigation and supply from reservoir capacity can be counterbalanced from the simulated result without any hindrance.

Estimated capital costs of fish exclusion technologies for hydropower facilities.

Hydropower is a reliable source of renewable energy, and its future expansion is likely to be in the form of either smaller new stream development (NSD) projects or powering existing non-powered dams. Thresholds for entrainment risk to fish and the requirements for fish exclusion at hydropower facilities often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders, but little quantitative information is present within the literature regarding the specific costs of fish exclusion measures. Cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening were identified using keyword searches of an existing environmental mitigation cost data set and manual extraction from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 p.m.&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens and represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with NSD projects. Results indicate highly variable costs are associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1-2 in.). These data provide an initial baseline for estimating exclusion costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects.

Assessing the impact of river connectivity on fish biodiversity in the Yangtze River Basin using a multi-index evaluation framework.

The Yangtze River Basin, the world's third-largest river basin and a hot spot for global biodiversity conservation, is facing biodiversity crisis caused by reduced river connectivity. The deterioration arises from four dimensions: longitudinal, lateral, vertical and temporal. However, limited research has quantified the spatiotemporal connectivity of the Yangtze River Basin and further evaluated the consequent impact on fish biodiversity. In our study, a multi-index evaluation framework was developed to assess the variations in the four-dimensional connectivity of the Yangtze River Basin from 1980 to 2020, and fish biodiversity affected by reduced connectivity was detected by environmental DNA metabarcoding. Our results showed that the Yangtze River Basin suffers from a pronounced connectivity reduction, with 67% of assessed rivers experiencing deteriorated connectivity in recent years. The lost fish biodiversity along the river reaches with the worst connectivity was likely attributed to the construction of hydropower plants. The headwaters and the downstreams of most hydropower plants had a higher fish biodiversity compared with reservoirs. The free-flowing reaches in the downstream of the lowest hydropower station, had higher lotic fish abundance compared with that in the upstream. As for the entire Yangtze River Basin, 67% of threatened fish species, with 70% endemic species, were threatened by reduced river connectivity. Our result indicates that the massive loss of river connectivity changes the spatiotemporal patterns of fish community and threatens protected fish. More effective measures to restore the populations of affected fish in rivers with reduced river connectivity are required.

Sustainability assessment of small hydropower from an ESG perspective: A case study of the Qin-Ba Mountains, China.

Small hydropower (SHP) has made significant contributions to economic and social development in rural and remote mountainous regions. However, the adverse ecological-environmental impacts resulting from the SHP sector and challenges in hydropower management have become major areas of concern. From an Environmental, Social, and Governance (ESG) perspective and using three SHP stations (GXD, WZL, and SJB) in the Qin-Ba Mountains as case studies, we constructed a sustainability assessment system comprising 18 indicators across three dimensions. The hesitant fuzzy linguistic term sets (HFLTSs) and cloud models were employed to determine the sustainability level of SHP by characterizing the hesitancy of the evaluator and the uncertainty of the evaluated data. (1) The ecological-environmental protection (E) dimension was assigned the greatest weight, followed by the dimensions of social responsibility contribution (S) and corporate governance management (G). The weights of certain indicators, including the water qualification rate, river morphology maintenance, guaranteed rate of instream flow, comprehensive utilization, and production safety standardization grade were relatively high, conforming to the current context of green development prioritization in which ecological-environmental protection is of the utmost importance. (2) The overall sustainability levels of all three SHP stations were "good", with the E-dimension contributing the most and the G-dimension contributing the least to the sustainability goal. (3) The GXD, WZL, and SJB stations were ranked first, second, and third, respectively, in terms of their sustainability scores. This study provides an innovative perspective for the sustainability assessment of SHP. The evaluation method can be generalized to encompass multi-attribute decision-making problems. The findings of this study can aid in addressing the shortcomings associated with SHP development and promote sustainability within the SHP industry.