A sweeping 25-year analysis of China’s Yellow River Basin shows that the region’s water resources, energy systems, land use, and carbon emissions have grown steadily more coordinated since 2000, yet the improvement masks a rigid east-west divide and a stubborn dependence on coal. Researchers at North China University of Water Resources and Electric Power built a composite index tracking the four systems across nine provinces and regions from 2000 to 2024, then applied obstacle-degree and geographical detector models to pinpoint what holds the basin back. Their results, published in Frontiers in Ecology and Evolution, show that every subsystem and the combined water-energy-land-carbon index rose continuously over the study period. But the gains are unevenly distributed: Shandong and Henan in the downstream east form the core of high-level coordination, while upstream Qinghai and Sichuan remain the basin’s principal bottleneck areas. Coal production emerged as the single most constraining factor basin-wide.

The Yellow River Basin is China’s second largest, stretching from the Qinghai-Xizang Plateau, where source elevations generally exceed 3,000 meters, down to the North China Plain at 20 to 200 meters. It spans forests, grasslands, wetlands, deserts, and glaciers, and holds abundant reserves of coal, oil, natural gas, wind, and solar energy, making it a core zone for energy production and territorial development. Water, however, is chronically scarce. Between 2003 and 2022, the basin’s surface water resources fluctuated between 39 billion and 74.6 billion cubic meters, while groundwater held roughly steady at 19 billion to 24 billion cubic meters. Provincial endowments differ sharply: Sichuan averaged 253.852 billion cubic meters of water resources and Qinghai 75.795 billion, whereas downstream Shandong averaged 31.943 billion and Shanxi just 11.452 billion. Ningxia recorded the basin’s lowest average at only 1.028 billion cubic meters, underscoring the region’s structural water deficit.

To quantify coordination among the four systems, the team assembled panel data from the statistical yearbooks, water resources bulletins, environmental quality bulletins, and China energy bulletins of the nine provinces for 2000 to 2024. Indicators were classified as positive or negative and normalized to remove unit effects. The researchers then applied an improved entropy weighting method, which corrects biases that arise when indicators are correlated, and combined it with subjective weights from a three-scale analytic hierarchy process to produce hybrid index weights. The resulting Water-Energy-Land-Carbon comprehensive index, or WELCNI, integrates subsystem scores for water, energy, land, and carbon into a single measure of coupling and coordinated development. An obstacle degree model identified which individual indicators most restrict the composite system, while a geographical detector, using factor and interaction detection, tested how strongly potential drivers explain the spatial variation in coordination levels across provinces.

The calculated weights reveal which dimension carries the most influence: water resources scored 0.3017, energy 0.27975, carbon 0.2567, and land 0.1615. From 2000 to 2006, subsystem scores across the basin sat in a low range of roughly 0.01 to 0.54, exposing a weak development foundation. Extremes were stark in 2000: Shandong’s water subsystem scored 0.4687 against Qinghai’s 0.0421, a gap of 0.4266, while Shanxi led energy at 0.2940 and Henan led land at 0.5143. The carbon subsystem showed an inverted pattern, with Qinghai highest at 0.2991 and Henan lowest at 0.0242. Instability marked the early years, as Qinghai’s and Sichuan’s water scores fell to 0.0136 and 0.0155 in 2006, the period’s lowest values. From 2006 to 2018 the scores climbed rapidly; by 2018, Shandong’s and Henan’s water subsystems reached 0.7478 and 0.7423, and every province’s carbon score exceeded 0.41.

The composite WELCNI followed a stepped trajectory through three stages. In the low-speed accumulation phase from 2000 to 2012, basin scores ranged from 0.0759 in Shanxi to 0.3438 in Shandong, an inter-provincial gap of 0.2679 that reflected fragmented, unbalanced development. By 2012, Shandong and Henan had reached 0.5462 and 0.5204, entering medium-level coordination first, while Qinghai, Sichuan, and Gansu remained between 0.2000 and 0.2600. The rapid transition period from 2012 to 2018 proved the core window for upgrading coordination quality: Shandong’s composite score hit 0.6663 in 2018, Henan, Shanxi, and Shaanxi all exceeded 0.5400, and only Qinghai and Sichuan stayed below 0.4000. In the final stage from 2018 to 2024, growth slowed as the focus shifted to quality. By 2024, all nine provinces scored above 0.4000, led by Shandong at 0.7270, Henan at 0.6725, and Shanxi at 0.6300.

Space matters as much as time. Throughout the study period the basin held a stable three-tier gradient, strong in the east, transitional in the center, and weak in the west. Shandong and Henan, the first tier, recorded composite score increases of 0.3832 and 0.3855 respectively between 2000 and 2024, the fastest growth in the basin, and maintained high scores across all four subsystems. The second tier, comprising Shanxi, Shaanxi, Inner Mongolia, Ningxia, and central Gansu, showed a late-stage acceleration: after 2015 their growth rates ranked among the highest, steadily narrowing the gap with the eastern core. Shanxi and Shaanxi stood out for quality improvements, while Ningxia and Gansu progressed steadily and evenly. The third tier, Qinghai and western Sichuan, gained 0.2573 and 0.3045 respectively over the 25 years, yet remained constrained by geography, resource endowments, and industrial structure, keeping them at the downstream end of basin coordination.

Each subsystem followed its own evolutionary logic. The water system achieved the most dramatic improvement, reversing the extremely low western coordination levels of the early period, though Qinghai’s water shortcomings persisted throughout. The energy subsystem was marked by significant early differentiation, with central and western energy-rich provinces experiencing fluctuating scores amid industrial restructuring; after 2015, coordination levels converged across the region. The land system served as the basin’s stable foundation, with the highest initial levels and a continuously narrowing provincial gap, providing consistent support for the composite system. The carbon subsystem underwent a full spatial reversal: early on, western provinces scored higher while eastern provinces were weighed down by industrial carbon pressure, but as low-carbon policies took hold, the pattern flipped to high in the east and low in the west. By 2024, all four subsystem scores across the basin exceeded 0.39.

The obstacle analysis produced a clear hierarchy of constraints: energy, then water resources, then carbon emissions, then land. Coal production registered consistently high obstacle degrees and stood out as the core common obstacle factor across the entire basin, with total energy consumption and unit GDP energy consumption also exerting strong constraints, a signature of the region’s heavy dependence on fossil energy. In the water dimension, total water resources and per capita water resources ranked at the forefront, confirming that insufficient endowment, rather than management details, is the secondary bottleneck; water supply guarantee, soil erosion, and groundwater indicators constrained less, and ecological water replenishment least. Land indicators fell in the medium-to-low range, with soil and water conservation treatment area and forest coverage the least constraining. Among carbon indicators, total and per capita emissions hindered more than emission intensity. Spatially, Henan showed the highest obstacle coefficients and Gansu the least, while the middle reaches faced balanced energy and water constraints.

The geographical detector results added a crucial layer: obstacle factors do not act independently. Pairwise interaction q-values ranged from 0.41 to 1.00, and every paired interaction explained more spatial variation than the corresponding single factors, an inherent mathematical property of the model that, as the authors caution, indicates statistical synergy rather than proven causal coupling. Per capita water resources showed the strongest interactions with total and per capita carbon emissions; coal production interacted strongly with total water resources and hydropower generation; and the energy self-sufficiency rate paired prominently with coal production and total carbon emissions. Coal production, total energy consumption, and total carbon emissions acted as node factors, maintaining interaction q-values above 0.55 with most other indicators and radiating influence across the basin’s constraint network. The lone exception was unit GDP energy consumption, whose weak linkages made it the only largely independent constraint factor in the analysis.

The findings point toward multi-factor collaborative governance rather than single-dimension management. The authors recommend an integrated basin-wide mechanism that breaks inter-provincial administrative barriers, prioritizes differentiated coal capacity control as the core obstacle, and addresses water endowment shortages through cross-basin allocation and water-saving renovation in industry and agriculture. Zoned strategies follow the gradient: upstream Qinghai and Sichuan should emphasize ecological protection, water conservation, and carbon sink enhancement while moderating energy extraction; the coal-producing middle reaches must coordinate clean energy transformation with soil and water conservation; and the downstream should accelerate industrial upgrading and intensive land use. Because water, energy, and carbon constraints interact strongly, the authors argue that development projects should undergo joint assessment of water carrying capacity, land suitability, and carbon impact. The study remains an observational, index-based analysis of provincial panel data, so its interaction findings describe statistical associations rather than demonstrated causal mechanisms.

Subject of Research: Coupling and coordinated development of the water-energy-land-carbon system across nine provinces of the Yellow River Basin, with obstacle factor analysis

Article Title: Coordinated development of the “water-energy-land-carbon” system in nine provinces and regions of the Yellow River Basin and analysis of obstacle factors

Article References: Wang, M., Li, J., & Yang, M. (2026). Coordinated development of the “water-energy-land-carbon” system in nine provinces and regions of the Yellow River Basin and analysis of obstacle factors. Frontiers in Ecology and Evolution, 14, Article 1932520. https://doi.org/10.3389/fevo.2026.1932520

Image Credits: AI Generated

DOI: 10.3389/fevo.2026.1932520

Keywords: Yellow River Basin, water-energy-land-carbon, coupling coordination, obstacle degree model, geographical detector, coal production, carbon emissions, water resources, entropy weighting, regional development, China, sustainable development