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Review

A Review on Ecological and Environmental Impacts of Pumped Hydro Storage Based on CiteSpace Analysis

by
Hailong Yin
1,†,
Xuhong Zhao
1,†,
Meixuan Chen
2,
Zeding Fu
3,4,
Yingchun Fang
5,
Hui Wang
1,
Meifang Li
1,
Jiahao Luo
1,
Peiyang Tan
5 and
Xiaohua Fu
1,5,*
1
Center for Ecological Environment Management and Evaluation, Central South University of Forestry and Technology, Changsha 410004, China
2
Hunan Normal University, Changsha 410081, China
3
Yangtze River Dongting Lake Water Conservancy Affairs Center, The Water Resources Bureau of Yueyang, Yueyang 414000, China
4
School of Metallurgy and Environment, Central South University, Changsha 410012, China
5
Hunan Jiangshan Chunjin Technology Co., Ltd., Changsha 410004, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Water 2025, 17(18), 2752; https://doi.org/10.3390/w17182752
Submission received: 4 August 2025 / Revised: 10 September 2025 / Accepted: 12 September 2025 / Published: 17 September 2025
(This article belongs to the Section Hydraulics and Hydrodynamics)
Browse Figures
Versions Notes

Abstract

This study conducted a systematic review of 222 research articles (2014–2024) from the Web of Science Core Collection database to investigate the ecological and environmental impacts of pumped hydro storage (PHS). Utilizing CiteSpace 6.1R software for visual analysis, the research hotspots and evolutionary trends over the past decade were comprehensively examined. Key findings include the following: (1) Annual publication output exhibited sustained growth, with China contributing 29.7% of total publications, ranking first globally. (2) Research institutions demonstrated broad geographical distribution but weak collaborative networks, as the top 10 institutions accounted for only 21.6% of total publications, highlighting untapped potential for cross-regional cooperation. (3) Current research focuses on three domains: ecological–environmental benefit assessment, renewable energy synergistic integration, and power grid regulation optimization. Emerging trends emphasize multi-objective planning (e.g., economic–ecological trade-offs) and hybrid system design (e.g., solar–wind–PHS coordinated dispatch), providing critical support for green energy transitions. (4) Post-2020 research has witnessed novel thematic directions, including deepened studies on wind–PHS coupling and life-cycle assessment (LCA). Policy-driven renewable energy integration research entered an explosive growth phase, with PHS–photovoltaic–wind complementary technologies emerging as a core innovation pathway. Future research should prioritize strengthening institutional collaboration networks, exploring region-specific ecological impact mechanisms, and advancing policy–technology–environment multi-dimensional frameworks for practical applications.

1. Pumped Hydro Storage and Energy Challenges

1.1. Pumped Hydro Storage Technology and Its Development

At the 21st United Nations Climate Change Conference (COP21) in 2015, the Paris Agreement was adopted by 178 global parties to combat climate change through greenhouse gas emission reduction, sparking a worldwide transition toward green and low-carbon energy systems. Pumped hydro storage (PHS), a mature large-scale clean energy storage technology, addresses electricity supply-demand imbalances by pumping water to upper reservoirs during off-peak periods and releasing it to generate power during peak demand.
Pumped hydro storage is a critical renewable energy storage technology (Figure 1) that stabilizes grid loads by leveraging gravitational potential energy to store and release electricity, while efficiently integrating intermittent and volatile wind and solar power. PHS offers multiple advantages, including high energy conversion efficiency, rapid response, large-scale storage capacity, long operational lifespan, and environmental friendliness, making it one of the most vital tools for achieving carbon emission reduction targets.
Compared to other energy storage technologies (e.g., lithium-ion batteries, compressed air energy storage), PHS relies on renewable water resources and emits no CO2 or pollutants during energy conversion, ensuring minimal environmental impact and superior sustainability. Although wind and solar energy systems produce zero carbon emissions, their inherent intermittency and volatility challenge grid stability—solar power is constrained by diurnal and weather conditions, while wind power exhibits seasonal fluctuations. PHS mitigates these issues through its energy storage-release cycle, effectively reducing minimum fluctuations in power output by [1] and demonstrating low life-cycle carbon emission intensity [2]. Additionally, PHS avoids dependence on rare metal resources, further enhancing its environmental sustainability.
The origins of PHS technology trace back to the late 19th century, driven by growing energy storage demands and technological advancements. The world’s first PHS plant, constructed in Switzerland in 1882, demonstrated remarkable efficacy and laid the foundation for global adoption. By 1950, 31 PHS plants were operational worldwide, with a total installed capacity of 1.3 GW. By the late 1960s, the United States led in PHS installed capacity, maintaining this position for over two decades. The 1973 and 1979 oil crises reduced reliance on fossil fuel power plants, prompting nations to prioritize nuclear energy. However, catastrophic accidents at the Three Mile Island (1979, USA) and Chernobyl (1986, USSR) nuclear plants triggered global reassessment of nuclear risks, leading developed countries to gradually phase out nuclear power and invest heavily in renewable alternatives, including hydropower. Pumped storage is currently the dominant form of energy storage worldwide, accounting for more than 90 per cent of the world’s installed energy storage capacity. By the end of 2024, the total installed capacity of pumped storage power plants in the world had exceeded 180 million kilowatts, mainly in China, the United States, Japan, Europe and other countries and regions.
In 2017, the International Renewable Energy Agency (IRENA) projected in its report Electricity Storage and Renewables: Costs and Markets to 2030 that global energy storage capacity would increase by 42–68% from 2017 levels by 2030, with PHS capacity growing by 40–50% [3]. China’s National Energy Administration outlined ambitious targets in its Medium- and Long-Term Development Plan for Pumped hydro storage (2021–2035): by 2025, operational PHS capacity is expected to double from the 13th Five-Year Plan period, exceeding 62 GW; by 2035, China aims to establish a modern, technologically advanced PHS industry capable of supporting large-scale renewable energy integration, while fostering globally competitive enterprises. As reported by the National Energy Administration on 7 February 2025, China’s operational PHS capacity surpassed 58 GW by the end of 2024, a significant increase from 45.79 GW in 2022, positioning the nation to achieve its 2025 target of over 62 GW.

1.2. Overview of Pumped Hydro Storage in Energy and Environmental Research

Through a systematic review of ecological and environmental impact studies on PHS over the past decade, this paper constructs an analytical framework encompassing three dimensions: energy system synergy, dual ecological–environmental effects, and policy-technology interdependencies. The focus on ecological impacts is motivated by significant discrepancies in existing literature regarding PHS’s environmental benefits, particularly its carbon reduction mechanisms, ecological compensation pathways, and technological optimization models, which remain unresolved. While photovoltaic (PV) and wind power are widely regarded as viable options for reducing energy-related environmental impacts and enhancing local energy security [4,5,6,7,8], studies reveal substantial variations in CO2 emissions across different grid power sources [9,10,11,12,13,14,15,16]. This complexity suggests that renewable/clean energy systems do not guarantee straightforward CO2 reduction mechanisms [17,18,19,20,21,22,23,24,25,26,27], a critical bottleneck in current energy transition policymaking.

1.2.1. Functional Role of PHS from an Energy System Synergy Perspective

PHS plays an irreplaceable role in regulating modern power systems. Martínez-Lucas et al. [28] demonstrated that frequency disturbances caused by wind power integration in islanded grids can be dynamically balanced via PHS. Virasjoki et al. [29] highlighted that ambitious renewable energy targets set by the EU and other regions necessitate energy storage technologies to improve economic and environmental outcomes. This regulatory advantage stems from PHS’s unique “energy time-shifting” capability. De Boer et al. [30] modeled that large-scale storage technologies like PHS optimize energy and environmental benefits by utilizing surplus electricity. Beyond power systems, PHS also offers freshwater storage advantages. Hunt et al. [31] proposed PHS as a cost-effective solution for short- and long-term energy storage, while Garcia et al. [32] showed that charging electric vehicles with excess PHS-generated power during low-demand periods reduces overall environmental impacts.
Decarbonizing power systems and enhancing environmental safety require optimized use of renewable energy. Hybrid renewable systems exhibit superior cost and environmental benefits compared to conventional energy sources [33,34,35,36,37,38,39,40,41,42,43], with large-scale storage facilities proving critical [44,45,46,47,48,49,50,51,52,53,54]. However, ecological impacts and deployment costs vary significantly across storage technologies [55,56,57,58,59,60,61], while intermittency and unpredictability remain major barriers to renewable adoption [62]. To address weather uncertainties, Elnozahy et al. [63] proposed hybrid systems combining batteries with supercapacitors, flywheels, PHS, or fuel cells, though such configurations incur high costs and exacerbate battery-related environmental impacts. Life cycle assessments reveal that electrochemical storage systems (e.g., lithium-ion batteries) impose greater environmental burdens than mechanical systems due to limited cycle lifetimes [64,65], reinforcing PHS’s suitability for large-scale deployment. PHS-integrated renewable systems also demonstrate cost advantages over traditional generation. Cheng et al. [66] argued that fossil gas reliance is unsustainable long-term, with PV–wind–PHS hybrid models achieving levelized electricity costs of $0.044–0.053/kWh in Bolivia, far exceeding supply-demand balancing requirements. De Moura et al. [67] found PHS in Brazil to reduce CO2 emissions by 23% at 84% of the cost of hydrogen-based alternatives. Rogeau et al. [68] emphasized PHS’s continued dominance as the most mature grid-scale storage technology amid growing renewable penetration.

1.2.2. Dual Ecological–Environmental Effects

Studies confirm PHS’s multi-scale ecological gains. Javed et al. [69] prioritized PV–wind–PHS–diesel and PV–wind–PHS hybrid systems for emission-conscious renewable integration. Sanna et al. [70] demonstrated that coupling PV-PHS with reverse osmosis desalination reduces greenhouse gas emissions per unit of freshwater by 46.8% compared to PV-battery systems. Katsaprakakis et al. [71] highlighted PHS’s contributions to regional development and climate resilience. Moreno-Leiva et al. [72] proposed seawater-based PHS-copper production systems to minimize the environmental footprint of copper, a critical resource for global energy transitions.
Ecological impacts during the construction and operation phases exhibit complex characteristics. Li et al. [73] developed a cloud model-based fuzzy comprehensive evaluation method and coupling relationship model to analyze the interactions between PHS and ecosystems, identifying four factors—construction costs, installed capacity, daily pumping volume, and average electricity consumption—that exert significant negative effects on coupling coordination. Casasso et al. [74] utilized groundwater models to reveal that underground power station construction in karst landscapes may alter hydrogeological conditions. Luna et al. [75] demonstrated that water supply systems, due to substantial energy consumption in pumping and water loss, impose significant environmental and energy burdens. Arena et al. [76] argued that ecological challenges during PHS construction are a key barrier to its broader adoption. While retrofitting abandoned mines (e.g., Guo et al. [77]) can mitigate land-use impacts, geological stability risks persist. These findings underscore the regional heterogeneity of ecological disruptions.

1.2.3. Synergistic Evolution of Policy and Technology

Several studies propose policy recommendations to advance PHS development. Zhang et al. [78] analyzed how China’s monitoring policies may influence PHS technological progress and provided actionable insights. Nibbi et al. [79] elaborated on policy frameworks to accelerate PHS deployment, emphasizing that government initiatives critically shape technological innovation. Globally, nations are prioritizing novel technologies through targeted programs. Emerging solutions are also overcoming traditional limitations: Silalahi et al. [80] demonstrated that PHS outperforms conventional storage technologies in cost-efficiency and performance, with off-river PHS systems in Indonesia achieving sustainable energy goals while minimizing environmental and social impacts [81].

1.2.4. Current Research Gaps and This Study’s Contributions

While existing literature highlights PHS’s technical advantages, ecological-economic impacts, and potential to enhance regional socio-economic development and cultural landscapes [82,83,84,85,86,87,88,89,90,91], three critical limitations persist: (1) Static Assessment Metrics: Most environmental evaluations rely on static indicators, neglecting dynamic life-cycle tracking (e.g., ignoring carbon emissions from battery recycling phases). (2) Fragmented Ecological Compensation Mechanisms: A unified ecosystem service valuation framework remains absent. (3) Inadequate Multi-Scale Synergy: Interactions between micro-project effects and regional ecological networks are poorly understood.
This study prioritizes ecological impacts for three reasons: (1) Ecological controversies dominate PHS project approvals, significantly constraining deployment. (2) Current environmental impact assessment systems inadequately address emerging PHS technologies. (3) Ecological civilization mandates necessitate novel evaluation paradigms.
Using CiteSpace to map research hotspots and evolutionary trends, our systematic literature review reveals that PHS ecological research is transitioning from single-technology assessments to complex system analyses. A comprehensive evaluation framework integrating ecological carrying capacity, climate resilience, and social acceptance is urgently needed. Subsequent chapters will explore PHS’s synergistic evolution with regional ecosystems, providing theoretical foundations for green power station assessments.

2. Research Tools and Selection

2.1. Comparative Analysis of Classic Literature Research Tools

The selection of research tools profoundly impacts study efficiency and analytical depth. This study compares six literature analysis tools—CiteSpace, VOSviewer, Gephi, HistCite, NVivo, and Atlas.ti—across functional characteristics, application scenarios, and usability thresholds to provide methodological guidance for researchers. As the core tool, CiteSpace demonstrates unique advantages in dynamic knowledge mapping, hotspot evolution tracking, and multi-dimensional network analysis. Its burst detection and timeline slicing capabilities enable precise identification of long-term trends in PHS ecological impact research. Through betweenness centrality calculations, CiteSpace identifies pivotal literature and academic hubs, offering robust data support for framework development. A comparative analysis of these tools is presented in Table 1, emphasizing CiteSpace’s distinctive functionalities.

2.2. Core Advantages and Selection Rationale of CiteSpace

CiteSpace, a Java-based information visualization software, employs co-citation analysis and pathfinder network scaling algorithms to quantify domain-specific literature collections, identify critical evolutionary pathways and knowledge inflection points, and visualize latent driving mechanisms and research frontiers through graphical mapping [92]. Analyzing citation networks and co-authorship relationships helps identify research hotspots, collaborative networks, and emerging trends, improving research quality and strategic decision-making.
This study utilizes CiteSpace 6.3 R1 for systematic analysis of PHS ecological impact literature, justified by its dynamic knowledge network resolution and multi-dimensional analytical capabilities. For instance, in renewable energy research, it has tracked burst cycles of emerging technologies (e.g., organic photovoltaics [93]). By generating time-sliced clustering maps, CiteSpace reveals phase-specific developmental characteristics, outperforming VOSviewer’s static network analysis and HistCite’s citation chain backtracking in dynamic trend identification. CiteSpace identifies core papers via betweenness centrality, superior to HistCite and Gephi, and integrates co-authorship, institutional collaboration, and keyword clustering networks to map research clusters geographically (e.g., institutional collaboration patterns in remote sensing change detection [94]). Keyword co-occurrence networks, enhanced by log-likelihood ratio (LLR) clustering and silhouette metrics, quantify thematic cohesion—capabilities unattainable with qualitative tools like NVivo or Atlas.ti. CiteSpace quantifies frontier directions through burst detection and time-zone views. For example, analyses of PHS economic evaluations under electricity market reforms [95] align closely with policy release cycles, whereas VOSviewer produces static keyword clouds lacking temporal insights.
Analysis of 222 publications confirms CiteSpace’s efficacy in elucidating ecosystem-level research linkages.

2.3. Operational Workflow of CiteSpace

CiteSpace facilitates academic network analysis through three stages: data import, network construction, and visualization (Figure 2).
Stage 1: Data Import:
Researchers import bibliographic data (e.g., BibTeX, EndNote, XML) into CiteSpace. The software preprocesses data by removing duplicates and invalid entries to build a structured dataset.
Stage 2: Network Construction
Using citation and co-citation relationships, CiteSpace constructs knowledge networks. Metrics like citation frequency and co-citation strength quantify inter-literature associations. Cluster analysis groups literature by thematic similarity, clarifying domain knowledge structures.
Stage 3: Visualization and Analysis
CiteSpace visualizes the constructed knowledge network for researchers, where node size, color, and other attributes encode bibliometric indicators such as citation frequency and centrality, enabling intuitive assessment of literature significance and influence. Additionally, CiteSpace offers analytical tools—including thematic evolution tracking and author collaboration mapping—to further explore research trends and cooperative relationships within the academic domain.

2.4. Data Sources

This study retrieved English-language publications from the Web of Science Core Collection database, focusing on the ecological and environmental impacts of PHS from 2014 to 2024. A total of 222 relevant articles were selected for analysis. CiteSpace 6.3 R1 was employed to visualize publication trends, institutional collaborations, and keyword co-occurrence patterns.

3. Results

3.1. Analysis of Publication Trends

The annual publication volume from 2014 to 2023 (Figure 3) demonstrates a pronounced upward trend in research on the ecological and environmental impacts of PHS, with a fitted curve R2 value of 87.61% (R2 ranges from 0 to 1; higher values indicate stronger model-data alignment, where values exceeding 0.8 denote high reliability). This trajectory can be categorized into three distinct phases:
Phase 1 (2014–2016): Research on PHS ecological impacts was in its infancy, characterized by low and stable publication output.
Phase 2 (2016–2019): China emerged as the global leader in PHS-related publications, driven by its strategic focus on advancing PHS technologies. The release of China’s 13th Five-Year Plan for Electric Power Development (2016–2020) by the National Energy Administration in 2016 significantly bolstered research investments. Concurrently, international attention to PHS ecological impacts grew, resulting in a steady annual increase in publications until 2020, when the COVID-19 pandemic caused a temporary decline.
Phase 3 (2020–2023): Post-pandemic recovery efforts prioritized PHS infrastructure to revitalize industrial activities, doubling publication volumes by 2022 compared to 2020. Global recognition of PHS as a clean energy storage solution accelerated research into its ecological impacts, aligning with energy transition goals to reduce fossil fuel dependence.

3.2. Regional and Institutional Analysis

3.2.1. Country/Region Analysis

Analysis of national/regional publication volumes reveals the influence of different countries in this field. As shown in Figure 4, China ranks first with 66 publications (29.7% of global output), underscoring its leading role in PHS research, driven by supportive energy policies.
In China, the 13th Five-Year Plan for Electric Power Development (2016–2020) explicitly prioritized “accelerating pumped hydro storage plant development,” backed by dedicated funding for key technologies. Subsequent studies (2017–2020) focused on variable-speed unit optimization [94,95,96] and hybrid energy storage systems [97,98]. Post-2021, the Medium- and Long-Term Development Plan for Pumped hydro storage (2021–2035) shifted research toward abandoned mine retrofitting for PHS [99,100,101,102,103] and ecology-energy synergy [104,105], with publications steadily increasing after 2020, Compared with countries such as the United States and the European Union, China is more inclined towards water conservancy and power (Table 2).

3.2.2. Institutional Analysis

Institutional analysis helps researchers identify leading entities, collaborative patterns, and research priorities within a specific field. By examining institutional collaborations, this approach reveals influential organizations and informs future research planning.
Based on CiteSpace 6.3 R1 analysis, the institutional collaboration network (Figure 5) comprises 214 nodes and 248 links, with a network density of 0.0109. Node size corresponds to publication volume, color indicates publication year, and connecting lines represent collaborative relationships. Key contributors include the Chinese Academy of Sciences (9 articles), Egypt Knowledge Bank (7 articles), National Center for Scientific Research (4 articles), Jagiellonian University (4 articles), and University of São Paulo (4 articles). Most active institutions are research organizations and universities, focusing on thermodynamics, earth sciences, chemistry, marine/freshwater biology, green technologies, and interdisciplinary fields.
Notably, even the most productive institution—the Chinese Academy of Sciences—accounts for only 4% of total publications (2014–2024). The top 10 institutions collectively contributed 48 articles (21.6% of total output), reflecting the broad, decentralized nature of PHS ecological impact research. Emerging collaborations (e.g., China University of Geosciences–China University of Mining and Technology; Natural Environment Research Council–University College London) highlight regional clusters, though isolated nodes indicate untapped partnership potential (Table 3).

3.3. Research Hotspot Analysis

Using CiteSpace 6.3 R1, keyword co-occurrence analysis of 222 English publications on PHS ecological impacts generated a clustering map with 512 nodes, 2166 links, and a network density of 0.0166. The modularity (Q value) and silhouette (S value) of the clusters were 0.498 and 0.8071, respectively. These metrics evaluate clustering validity: Q values range within [0, 1), where Q > 0.3 indicates significant modular structure; S > 0.5 suggests reasonable clustering, while S > 0.7 signifies high-confidence clusters [108]. The results confirm the robustness of the generated knowledge network.

3.3.1. High-Frequency Keywords

Combining the keyword co-occurrence network from Figure 6 and the frequency/centrality data in Table 4, the ecological and environmental impact assessment of PHS over the past decade has predominantly focused on keywords such as “renewable energy,” “performance,” “energy storage,” “optimization,” “model,” “design,” “system,” “wind power,” “technology,” “climate change,” “power generation,” and “impact.” Notably, research themes have concentrated on renewable energy integration (frequency: 28), energy storage optimization (frequency: 27), and system efficiency enhancement (frequency: 23), while keywords explicitly addressing ecological “impact” remain underrepresented (Table 4). This bias reflects a technology-driven research paradigm, with ecological dimensions significantly marginalized.
The keyword “climate change” exhibits high centrality (Table 4) but low frequency, suggesting that existing studies often oversimplify ecological issues through a climate adaptation lens—for instance, equating carbon emission reduction with ecological protection [67]. In reality, PHS deployment may induce critical ecological challenges, such as localized biodiversity loss and terrestrial vegetation destruction in reservoir inundation zones [109], yet these topics are absent in keyword networks.
The dominance of “design” (centrality: 0.23) and “optimization” (centrality: 0.15) over ecological metrics is further evidenced by case analyses. For example, the Atacama Desert PHS project in Chile [110] validated steel price impacts on costs through sensitivity analysis but failed to quantify soil and water loss during construction. Similarly, a case study in Northwest China [111] identified increased curtailment due to uncoordinated development but omitted assessments of its effects on fish habitat connectivity in watersheds.
Methodological Limitations:
Temporal Narrowness: Environmental analyses predominantly focus on operational-phase carbon emissions, neglecting construction-phase ecological disturbances. For instance, reservoir construction may alter groundwater dynamics and degrade adjacent wetlands [112], yet “hydrology” is absent from high-frequency keywords.
Model Simplification: Strong associations between “modeling” and “system” reflect a bias toward engineering optimization, with limited integration of ecological process coupling. Most optimization models [113] prioritize electricity supply-demand balance while ignoring ecological flow thresholds as constraints. Stakeholder surveys for the UK’s North Sea low-head project [114] prioritized structural safety and economic viability, with no discussion of ecological risk mitigation—a stark contrast to the high frequency of “technology” (13), underscoring the disconnect between technical and ecological dimensions.
Recommendations for Future Research:
Integrate ecological indicators such as biodiversity and habitat fragmentation into evaluation frameworks. For example, Copula models [115] can quantify nonlinear relationships between reservoir operations and ecological responses, enabling their integration into system optimization.
Enhance dynamic ecological simulations, as evidenced by Brazil’s evaporation control through reservoir depth adjustments [31], which should inform policy-driven ecological compensation strategies.
Conduct comparative LCA to evaluate basin-scale ecological footprints of PHS versus battery storage systems [116], incorporating habitat restoration costs to shift citing criteria from terrain suitability to ecological priority.
While researchers emphasize improving system efficiency and climate resilience through advanced design and operational optimization, direct discussions of ecological impacts remain sparse. The prominence of renewable energy and energy storage underscores the field’s focus on addressing renewable integration challenges. However, the weak representation of ecological themes in keyword networks highlights the urgent need to deepen interdisciplinary linkages and embed ecological metrics into PHS research frameworks.

3.3.2. Keyword Clustering

The keyword clustering network generated by CiteSpace 6.3 (Figure 7) reveals three core clusters in PHS research: multi-objective optimization (Cluster ID 0), hybrid power systems (Cluster ID 1), and energy storage (Cluster ID 2), which form a technology-dominated network through high-weight connections. In contrast, ecological themes such as global warming potential (Cluster ID 9) and carbon neutrality (Cluster ID 8) occupy peripheral positions with sparse connectivity to technical clusters.
The low weight of global warming potential (Cluster ID 9) reflects fragmented carbon accounting practices. Sadhukhan et al. [117] demonstrated that while PHS reduces renewable curtailment (e.g., increasing renewable penetration by 13–22% in southern UK regions), reservoir construction disrupts local ecosystem integrity, particularly in biodiversity hotspots. Ba-abbad et al. [118] proposed mitigating ecological risks in Saudi Arabia’s seawater-based PHS systems through GIS-guided site selection (e.g., deep-sea discharge zones) to minimize hypersaline wastewater impacts on coastal ecosystems.
Dynamic ecological coordination gaps further compound these issues. Qiu et al. [119] projected a 30.6% increase in PHS potential density on the Tibetan Plateau under RCP 8.5 scenarios but warned of downstream hydrological cycle disruptions and runoff imbalance risks. The absence of direct links between carbon neutrality (Cluster ID 8) and hybrid power systems (Cluster ID 1) underscores the decoupling of decarbonization technologies (e.g., wind-PV hybrids) from hydro-ecological dynamics. For example, Cheng et al. [66] emphasized that uncoordinated reservoir level management in Bolivia’s high-renewable systems exacerbates wetland degradation in arid regions.
Inadequate ecological quantification persists in LCA. Hasan et al. [120] critiqued current PHS-LCA frameworks for overlooking methane emissions (CH4) from tropical reservoirs—2–3 times higher than fossil systems due to anaerobic decomposition [121]—and biodiversity loss. Casarin et al. [122] identified fish migration barriers caused by turbine gate adjustments in Sardinia’s hybrid PHS systems, but few existing studies have minimized such direct ecological costs. Frequent maintenance and dredging activities caused by mechanical wear, such as turbine abrasion (as evidenced by China’s Three Gorges Dam case), not only consume resources but also cause secondary ecological disturbances like sediment resuspension. The quantification of such indirect environmental costs remains critically understudied. To address this disconnect between technological and ecological dimensions, research on technology-ecology synergy pathways is critical. For instance, Rasool et al. [123,124] developed a grid-balancing hybrid storage model integrating PHS with batteries, reducing reservoir footprints by 18–25% while maintaining ecological thresholds.
This study shows that pumped storage research has a clear main direction but lacks interdisciplinary integration (Table 5). The main research challenge stems from the lack of effective theoretical correlation and methodological inter-embedding between the clustering groups, rather than the maturity of their internal development.
Cluster analysis reveals a significant disconnect between technological and ecological dimensions in PHS research. Core gaps include ecological indicators are not integrated into optimization frameworks; macro-level carbon neutrality goals lack coordination with micro-level assessment tools; and isolated fields such as geothermal exchange and exergy analysis remain poorly integrated with mainstream technologies. Future studies should develop techno-economic–ecological coordinated optimization models that incorporate ecological indicators such as biodiversity and water stress. Life-cycle environmental impacts should be integrated into power station planning and operational decision-making. A dynamic assessment framework should be established to quantify the value of isolated research fields. These efforts will promote interdisciplinary collaboration and facilitate pumped hydro energy storage to become a key node in integrated energy-environment systems.

3.3.3. Keyword Burst Detection

The keyword burst network (Figure 8) demonstrates distinct temporal differentiation and interdisciplinary intersections in PHS ecological research, systematically revealing its dynamic evolution through temporal distribution and burst intensity.
Phase 1 (2014–2017): Foundational Functional Exploration
Early studies focused on the fundamental functionalities of PHS technology, with ecological impacts preliminarily implied through associated keywords.
“Cycle” (burst strength: 1.56, 2014) and “simulation” (1.91, 2014) dominated research on cyclic operation modeling and system efficiency optimization, such as peakshaving capacity analysis using simulation tools.
“Carbon dioxide” (1.91, 2015) signaled emerging interest in PHS’s low carbon attributes, laying groundwork for comparative carbon emission analyses against conventional energy systems.
“Biological carbon pump” (1.19, 2016) hinted at aquatic carbon cycling mechanisms, indirectly supporting subsequent ecological effect assessments.
Phase 2 (2018–2020): Systematic Ecological Impact Assessment
The burst of “pumped hydro storage” (1.22, 2018) marked the institutionalization of ecological impact studies.
“Life cycle assessment” (1.92, 2018) catalyzed systematic evaluations of PHS’s environmental footprint, including land-use impacts during construction, water resource consumption in operation, and ecological restoration needs post-decommissioning, such as quantifying long-term vegetation loss in reservoir inundation zones.
“Impacts” (1.1, 2020) reflected direct analyses of localized ecosystem disturbances (e.g., eutrophication risks, fish habitat alterations), though limited data often restricted findings to indirect metrics (e.g., carbon emissions) or model simulations.
“Temperature” (2.59, 2020) highlighted research on reservoir thermal stratification effects on downstream water temperatures and aquatic ecosystems.
The combination of “integration” (1.92, 2018) and “wind power” (2014 burst) underscored hybrid renewable systems’ role in reducing fossil energy dependence and associated ecological burdens.
Phase 3 (2021–Present): Methodological Diversification and Technological Synergy
“Solar energy” (2.34, 2022) and “organic Rankine cycle” (1.25, 2022) emphasized PHS’s integration with solar energy and industrial waste heat recovery technologies.
“Model” (1.54, 2021) and “plants” (1.25, 2022) marked empirical approaches to quantify long-term ecological impacts, including hydrological modeling of soil erosion control and experimental analyses of wetland vegetation recovery under reservoir scheduling.
“Tool wear” (1.25, 2022) revealed ecological costs linked to equipment durability, such as chemical pollutant leakage risks from frequent maintenance or material abrasion impacts on reservoir water quality.

3.3.4. Temporal Evolution of Keywords

Using CiteSpace 6.3 R1 software, we conducted temporal network analysis on keyword clusters in PHS environmental impact research publications (2014–2024), with visualization results presented in Figure 9.
Research on the ecological impacts of pumped hydro energy storage exhibits distinct stage-specific characteristics, closely linked to global policy orientations and technological applications. The temporal evolution of keyword clustering reflects research priorities within specific timelines. Keywords such as “wind power generation,” “carbon dioxide,” and “life cycle assessment (LCA)” prominently emerging before 2020 indicate early research focused on the macro-level benefits of renewable energy replacing fossil fuels. This aligns with policy targets such as the Paris Agreement (2015) and the EU’s 2030 Climate and Energy Framework. Notably, the EU’s mandate requiring LCA for energy storage projects (European Commission, 2019) [124] has driven studies on the full life-cycle carbon footprint of PHS.
Post-2022, emerging keywords like “temperature,” “vegetation,” and “solar energy” correspond to national policies emphasizing ecological protection. For example, China’s Medium- and Long-Term Development Plan for pumped hydro storage (2021–2035) [3] explicitly integrates “vegetation recovery rate” and “thermal stratification control” into environmental impact assessment criteria, shifting research toward micro-scale ecological effects.
The highest burst intensities for “performance” (6.82) and “management” (6.35) reveal the tension between technological efficiency and ecological governance. While the U.S. Bipartisan Infrastructure Law (2021) [125] funded PHS R&D, litigation against California projects due to wetland loss from reservoir expansion highlights policy-ecology conflicts. The EU’s Nature Restoration Act (2022) requiring 5% of PHS water areas as biodiversity habitats has redirected research on “algorithm” and “model” toward multi-objective ecological constraints.
The sustained prominence of “solar energy” (burst intensity: 5.91, 2022–2024) correlates with solar- PHS integration policies. China’s 14th Five-Year Plan for New Energy Storage [126] promotes hybrid wind- PHS -solar systems, while Saudi Arabia’s Vision 2030 focuses on desert-based PHS -desalination complexes. In contrast, Europe’s land scarcity prioritizes low-head PHS technologies, as reflected in keywords like “blade wear” and “organic Rankine cycle”.
The keyword “cycle” underscores PHS’s long-term ecological impacts, yet current policies (e.g., IHA’s Sustainability Guidelines for PHS (2023) [127]) emphasize short-term emission reduction without quantifying cumulative ecological thresholds. Future research must integrate “simulation” and “hybrid systems” to model policy-ecology linkages, supporting global ecological admission criteria for PHS.

4. Conclusions and Recommendations

4.1. Research Conclusions

Based on 222 English publications addressing the ecological impacts of PHS retrieved from the Web of Science Core Collection database, this study employed CiteSpace 6.3 R1 to visualize annual publication trends, institutional collaborations, and keyword networks. Key findings are summarized as follows:
Publication Volume: Global annual publication volume has shown a steady increase, with China contributing the highest number of studies, reflecting both growing international attention to PHS ecological impacts and China’s leadership in advancing PHS-related research.
Institutional Collaborations: Leading research institutions predominantly include national academies and top-tier universities, with robust inter-institutional collaboration networks indicating strong governmental prioritization and active international knowledge exchange.
Keyword Analysis: The three highest-frequency keywords—“renewable energy,” “energy storage,” and “performance”—highlight the interdisciplinary nature of PHS ecological studies, emphasizing its role in enabling renewable energy transitions. Hybrid systems integrating wind, solar, and PHS are identified as dominant research frontiers.
Temporal Shifts: Research priorities have dynamically evolved over the past decade, driven by advancements in energy technologies, material sciences, and policy interventions.
Keyword evolution reveals that policy directives and technological demands jointly propel PHS development. With China’s dual-carbon goals and the global energy transition, PHS has emerged as a critical technology for stabilizing renewable energy fluctuations. Research foci have shifted from early single-technology modeling (e.g., wind- PHS coupling) toward multi-dimensional optimization, including complementary utilization of solar–wind–hydro energy, hybrid energy storage configurations, and life-cycle environmental assessments. However, as research and practical application advance, hybrid energy storage systems face several risks, including interface and coordination risks, increased system complexity, and the need for economic re-evaluation. Such challenges have become critical bottlenecks to large-scale deployment. It is essential to incorporate systematic risk prevention and control measures into development strategies.
Global development stages vary significantly across countries, leading to distinct technological pathways and priorities. Advanced economies like the EU focus on large-scale optimization and tech upgrades, tackling challenges like boosting system efficiency, reducing life-cycle environmental impacts, and integrating high-penetration renewables. Meanwhile, many developing countries are in the technology introduction and planning phase, prioritizing resource surveys, lowering financing costs, and obtaining reliable tech suited to local conditions. International case studies further demonstrate that scaling PHS needs to break through geographical and resource constraints and match local development stages. For instance, the EU has demonstrated technological innovation in the context of high-density infrastructure by enhancing grid flexibility through low-head PHS (LH PHS) technologies [116], while Southeast Asian countries repurpose abandoned mining sites for “brownfield energy storage projects [128],” to provide a viable low-cost, low-environmental-impact pathway for developing countries. These practices demonstrate the feasibility of technological innovation and resource reuse.

4.2. Development Recommendations

Promote Hybrid Energy Storage Systems with Multi-Scenario Adaptability. Single-technology solutions struggle to meet complex energy demands. Future research should explore synergistic models integrating PHS with electrochemical storage, flywheels, and other technologies. For instance, flywheel–PHS hybrid systems can reduce mechanical wear of equipment by 30% [125], while region-specific designs (e.g., small modular plants in high-altitude areas) enhance resource utilization efficiency [81].
Strengthen Policy Coordination and Cross-Regional Collaboration. PHS should be incorporated into national grid resilience planning, with synchronized approval mechanisms for renewable energy projects and storage facilities. The EU’s transboundary grid interconnection experience demonstrates that regional energy market integration reduces system costs by 12% [28]. Additionally, developing “water-energy-ecology” co-management frameworks—exemplified by Central Asia’s joint dispatch systems for improving water and energy storage efficiency [29]—could inform similar regions.
Establish Comprehensive Life-Cycle Environmental Assessment Frameworks. Current studies predominantly focus on techno-economic performance, neglecting dynamic ecological impact tracking. A standardized life-cycle assessment model covering construction, operation, and decommissioning phases is urgently needed to quantify carbon footprints and ecological disturbances. Research indicates that PHS exhibits significantly lower carbon emissions per unit of electricity generated (67–81 gCO2-eq/kWh) compared to hydrogen storage [67], yet biodiversity loss in reservoir areas requires mitigation through ecological compensation mechanisms.
Innovate Financing and Community Engagement Mechanisms. Reducing upfront investment barriers is critical for PHS deployment. Italy’s “energy storage-tourism” multi-purpose development model [118], which shares costs through diversified revenue streams, offers a replicable approach. Concurrently, establishing community co-governance platforms—such as Germany’s “public hearing-technical transparency” protocols for low-head PHS projects in the North Sea—can enhance social acceptance.

Author Contributions

All authors contributed to the study’s conception and design. Conceptualization, H.Y. and X.F.; Data curation, M.C. and M.L.; Formal analysis, Z.F. and X.F.; Funding acquisition, X.F. and Y.F.; Investigation, J.L.; Methodology, X.Z.; Project administration, P.T.; Resources, J.L. and Y.F.; Software, X.Z. and H.W.; Validation, Z.F. and M.C.; Writing—original draft, X.Z., Z.F. and X.F.; Writing—review and editing, M.L., H.W. and X.F. All authors will be updated at each stage of manuscript processing, including submission, revision, and revision reminder, via emails from our system or the assigned Assistant Editor. All authors have read and agreed to the published version of the manuscript.

Funding

This paper is a phased achievement of the Central Government’s Guiding Fund for Local Science and Technology Development, titled “Research and Engineering Demonstration on the Resource Utilization of Dredged Sediments from ‘One Lake and Four Rivers’ and Key Technologies for Reconstructing ‘Dual-Carbon’ Type Mining Areas” (2024ZYC0002), and “Technology and practice of ‘three-dimensional’ collaborative governance of rural ecological environment” (KDKJ2025WTKF01) and “Research on resource utilization technology of river and lake sediment in mine ecological restoration” (KDKJ2023KFJJA03).

Data Availability Statement

All important data for this manuscript are presented in the paper. If you have any questions, please contact the corresponding author.

Conflicts of Interest

Author Yingchun Fang and Peiyang Tan was employed by the company Hunan Jiangshan Chunjin Technology Co., Ltd. This is based on research interest and voluntary participation, and there is no conflict of interest with this paper. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Professor Fu Xiaohua works part-time as a technical advisor for the company, but this is of a voluntary nature and there is no interest relationship or conflict involved. This is hereby declared!

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Figure 1. Generalized Conceptual Diagram of the Operational Workflow for a Pumped Hydro Storage Plant.
Figure 1. Generalized Conceptual Diagram of the Operational Workflow for a Pumped Hydro Storage Plant.
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Figure 2. Flowchart of CiteSpace Operational Process.
Figure 2. Flowchart of CiteSpace Operational Process.
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Figure 3. The Trend in Annual Publications on Ecological and Environmental Impacts of PHS (2014–2023), with the Linear Trend Line (y = 4.1939x − 1.6667, R2 = 0.8761).
Figure 3. The Trend in Annual Publications on Ecological and Environmental Impacts of PHS (2014–2023), with the Linear Trend Line (y = 4.1939x − 1.6667, R2 = 0.8761).
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Figure 4. Top 10 Countries/Regions by Publication Volume (2014–2024).
Figure 4. Top 10 Countries/Regions by Publication Volume (2014–2024).
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Figure 5. Institutional Collaboration Network.
Figure 5. Institutional Collaboration Network.
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Figure 6. Keyword Co-occurrence (frequency) Network.
Figure 6. Keyword Co-occurrence (frequency) Network.
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Figure 7. Keyword Clustering Co-occurrence Network.
Figure 7. Keyword Clustering Co-occurrence Network.
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Figure 8. Keyword Burst Detection Map.
Figure 8. Keyword Burst Detection Map.
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Figure 9. Temporal Evolution and Keyword Cluster Network of PHS Environmental Impact Research (2014–2024).
Figure 9. Temporal Evolution and Keyword Cluster Network of PHS Environmental Impact Research (2014–2024).
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Table 1. Comparison of Literature Research Tools for Pumped Hydro Storage Analysis.
Table 1. Comparison of Literature Research Tools for Pumped Hydro Storage Analysis.
ToolsDescriptionKey FeaturesAdvantagesLimitations
CiteSpace 6.1RA bibliometric software for visualizing scientific knowledge structures, patterns, and distributions.(1) Multi-format data import;
(2) Advanced visualization;
(3) Cluster analysis and burst detection		(1) Unique dynamic hotspot tracking;
(2) Identifies critical academic nodes;
(3) Ideal for long-term network evolution		(1) Limited scalability for large datasets;
(2) Steep learning curve for advanced features
VOSviewer-1.6Open-source software (Leiden University) for constructing and visualizing bibliometric networks.(1) Multi-format compatibility (2) Network analysis;
(3) Visualization tools		(1) Handles large datasets efficiently;
(2) User-friendly interface		(1) Basic visualization options;
(2) Requires data preprocessing skills
Gephi-0.9.2Open-source network analysis and visualization platform for large-scale graph data.(1) Advanced network algorithms;
(2) Customizable visualization;
(3) Plugin support		(1) Deep analysis of complex networks;
(2) Active developer community		(1) Challenging for beginners;
(2) Resource-intensive for large datasets
HistCite Pro V2.1Citation analysis tool for mapping research trajectories and identifying seminal works.(1) Citation-focused analysis;
(2) Citation relationship mapping		(1) Rapid identification of influential literature;
(2) Clear field evolution mapping		(1) Exclusive compatibility with Web of Science (WoS) database;
(2) Limited functional scope
NVivo 12 PlusQualitative analysis software for unstructured/semi-structured data.(1) Multi-data type support;
(2) Coding/query tools;
(3) Qualitative analysis		(1) Robust qualitative data handling;
(2) Advanced data organization		(1) High licensing cost;
(2) Moderate learning curve
Atlas.ti 8.4Qualitative data analysis platform for text, images, audio, and video.(1) Multimodal data analysis;
(2) Flexible coding/visualization;
(3) Theory building		(1) Comprehensive qualitative tools;
(2) Supports collaborative research		(1) Complex interface;
(2) Requires significant training
Table 2. Comparative Analysis of PHS Policies and Research Priorities: China, the U.S., and the E.U. (2014–2024).
Table 2. Comparative Analysis of PHS Policies and Research Priorities: China, the U.S., and the E.U. (2014–2024).
Country/RegionKey PoliciesResearch Foci (2014–2024)Data Sources
ChinaMedium- and Long-Term PHS Development PlanVariable-speed units, mine-retrofitted PHS, ecological compensation|NationaNational Energy Administration [106]
USAInfrastructure Investment and Jobs Act (2021)Underground PHS, hybrid storage systems, financing modelsU.S. DOE [107]
EURenewable Energy Directive (2023 Revision)Policy simulation, cross-grid synergy, carbon tradingIRENA [3]
Table 3. Top 10 Institutions by Number of Publications on the Ecological and Environmental Impacts of PHS.
Table 3. Top 10 Institutions by Number of Publications on the Ecological and Environmental Impacts of PHS.
OrdinalNode NameNumber
1Chinese Academy of Sciences9
2Egyptian Knowledge Bank (EKB)7
3Centre National de la Recherche Scientifique (CNRS)4
4AGH University of Krakow4
5Universidade de Sao Paulo4
6Norwegian University of Science & Technology (NTNU)4
7Indian Institute of Technology System (IIT System)4
8North China Electric Power University4
9China University of Mining & Technology4
10Southeast University—China4
Table 4. Top 10 Keywords by Frequency and Centrality.
Table 4. Top 10 Keywords by Frequency and Centrality.
OrdinalFrequencyKeywordOrdinalCentralityKeyword
128renewable energy10.27performance
227energy storage20.23design
323performance30.21model
422optimization40.20energy storage
519system50.19renewable energy
618design60.17climate change
718energy70.15optimization
813model80.11cycle
913technology90.10system
1013simulation100.10wind power
Table 5. Cluster Analysis of PHS Research Based on Co-occurrence.
Table 5. Cluster Analysis of PHS Research Based on Co-occurrence.
Cluster TypeCluster NamingCurrent LimitationsIntegration Pathways
Core Research Clustersmulti-objective optimization
(Cluster ID 0)		Objective functions have a narrow scope. Ecological–environmental variables are predominantly set as boundary constraints rather than core optimization objectives in existing models, leading to suboptimal solutions in the ecological dimension.The computational core requires expansion. This involves integrating environmental assessment metrics (Clusters ID 8, Clusters ID 9) and key parameters from effect-based studies (Clusters ID 3, Clusters ID 4, Clusters ID 6) into the multi-objective optimization framework.
hybrid power systems
(Cluster ID 1)
energy storage
(Cluster ID 2)
carbon neutrality (Cluster ID 8)		Collaboration remains narrow. The co-occurrence between Cluster ID 8 and Clusters ID 1 and ID 2 primarily reflects preliminary integration with low-carbon energy technologies. It fails to incorporate broader ecological assessment dimensions.
Method Support Clusterpumped hydro energy storage
(Cluster ID 5)
global warming potential
(Cluster ID 9)
stochastic quasi-gradient methods
(Cluster ID 10)		Methodology-applications gap. Cluster ID 9 primarily co-occurs with Clusters ID 5 and ID 10, indicating its current function is limited to ex-post impact evaluation or serving conventional economic dispatch models. It fails to form an effective feedback loop with top-level strategic goals (Cluster ID 8), resulting in limited guidance for system design.Develop quantitative ecological constraints. This cluster should advance multi-dimensional environmental impact assessment models beyond global warming potential. The quantified results must be dynamically integrated into the optimization models of Cluster ID 0, establishing an iterative “assessment-optimization-reassessment” framework for design and management.
Low Connectivity Clustersground heat exchanger
(Cluster ID 3)
urban heat island
(Cluster ID 4)		Lacks integration with mainstream research. This cluster shows no significant co-occurrence with mainstream PHS technology development and evaluation systems. Functional coupling with core systems. Future work should explore integrating geothermal exchange and urban heat island effects into the comprehensive performance evaluation system of power stations.
exergy analysis
(Cluster ID 6)		Insufficient integration with engineering practice. This theoretical analysis method remains relatively isolated and has not been effectively incorporated into the multi-objective optimization processes of Cluster #0 or the systems engineering design workflows of Cluster ID 1.Advancing system efficiency analysis. Exergy efficiency can be introduced as a higher-level objective function into the optimization models of Cluster ID 0. By integrating with Clusters ID 1, ID 2, and ID 5, this approach enables precise identification and reduction in exergy destruction within the system.
photovoltaic
(Cluster ID 7)		Narrow system boundaries. Current studies predominantly treat photovoltaics merely as a power supply unit, without coordinated optimization of its life-cycle environmental footprint with the ecological impacts of PHS.Establish a PV-storage-environment coordinated planning framework.
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Yin, H.; Zhao, X.; Chen, M.; Fu, Z.; Fang, Y.; Wang, H.; Li, M.; Luo, J.; Tan, P.; Fu, X. A Review on Ecological and Environmental Impacts of Pumped Hydro Storage Based on CiteSpace Analysis. Water 2025, 17, 2752. https://doi.org/10.3390/w17182752

AMA Style

Yin H, Zhao X, Chen M, Fu Z, Fang Y, Wang H, Li M, Luo J, Tan P, Fu X. A Review on Ecological and Environmental Impacts of Pumped Hydro Storage Based on CiteSpace Analysis. Water. 2025; 17(18):2752. https://doi.org/10.3390/w17182752

Chicago/Turabian Style

Yin, Hailong, Xuhong Zhao, Meixuan Chen, Zeding Fu, Yingchun Fang, Hui Wang, Meifang Li, Jiahao Luo, Peiyang Tan, and Xiaohua Fu. 2025. "A Review on Ecological and Environmental Impacts of Pumped Hydro Storage Based on CiteSpace Analysis" Water 17, no. 18: 2752. https://doi.org/10.3390/w17182752

APA Style

Yin, H., Zhao, X., Chen, M., Fu, Z., Fang, Y., Wang, H., Li, M., Luo, J., Tan, P., & Fu, X. (2025). A Review on Ecological and Environmental Impacts of Pumped Hydro Storage Based on CiteSpace Analysis. Water, 17(18), 2752. https://doi.org/10.3390/w17182752

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