Multi-objective decision model for wastewater treatment technology selection based on machine learning.

Detecting farmland green production efficiency considering Sustainable Development Goals (SDGs) in the Yellow River Basin: Dynamics, drivers, and challenges

Comparative analysis of GAMLSS modeling approaches for nonstationary runoff dynamics in the Yellow River Basin of China

Impacts of land use patterns on seasonal water quality across spatial scales and river grades in the large-scale Yellow River Basin

Terrestrial water storage variations and drought characteristics in the upper yellow river basin revealed by joint GNSS-GRACE analysis

Tracking temporal dynamics trajectories and drivers of net primary productivity in the Yellow River Basin of China

Assessment of deficit irrigation impacts on water productivity and crop yield in the arid yellow river Basin using the SWAT model

Urban sprawl refers to the undesirable expansion of cities and the irrational exploitation of land resources. This study takes the Yellow River Basin as the research domain and measures the urban sprawl index of 73 prefecture-level cities in the basin from 2000 to 2020. Utilizing DMSP/OLS, NPP/VIIRS nighttime light data, and LandScan population data, the research applies the Theil index to examine urban sprawl levels and spatial heterogeneity among the upper, middle and lower reaches of the basin, as well as within individual cities. The results show that: (1) between 2000 and 2020, urban sprawl levels in the 73 prefecture-level cities within the Yellow River Basin demonstrated a consistent downward trend, with a spatial decrease observed from west to east; (2) the overall Theil index revealed regional disparities that gradually lessened over the years, with differences within the basin being significantly greater than those between its upper, middle, and lower sections; and (3) in terms of spatial heterogeneity, multiple prefecture-level cities in Qinghai Province, at the source of the basin, are primarily located in the “high high cluster” region, whereas the “low low cluster” is largely concentrated in the eastern downstream areas of the Yellow River. Sanmenxia City, located in the middle reaches, was long term the “high low cluster” zone, while the “low high cluster” zone was concentrated in Xining, Lanzhou, and Baotou cities in the upper reaches. Investigating urban sprawl in the Yellow River Basin contributes to advancing the sustainable development of the basin in a profound manner.

Abstract. Modeling the coupled human–natural systems (CHANS) is vital for understanding human–natural interactions and achieving regional sustainability, offering a powerful tool to alleviate human–water conflicts, ensuring food security, thereby supporting the region's pathway toward sustainable development. However, the scarcity of regional-scale CHANS models constrains progress in practical applications for regional sustainability. The Yellow River basin (YRB) is an ideal region for modeling regional CHANS due to its closely coupled human and natural systems, which are stressed by water and ecosystem fragility. Here, we developed the CHANS-SD-YRB model using the System Dynamics approach, integrating 10 sectors essential for modeling human-water interactions of the basin, including five human sectors (Population, Economy, Energy, Food, and Water Demand) and five natural sectors (Water Supply, Sediment, Land, Carbon, and Climate). The model can simulate evolution and feedbacks of the YRB CHANS annually at provincial and sub-basin scales, while conserving hydrological connectivity between sub-basins. The model can accurately reproduce historical CHANS dynamics, achieving strong quantitative agreement with historical data (R > 0.95 for human sectors and R > 0.7 for natural sectors), which supports its applicability for scenario analyses and future projections. We applied the model to explore human–natural system dynamics under a future baseline scenario, assuming the continuation of existing policies and climate projection under middle of the road scenario (SSP–RCP 2-4.5). The future projections (2021–2100) indicate that achieving sustainable development in the YRB will remain challenging, though economic growth and food security are expected to improve. Emerging issues, such as ecological–human water trade-offs, labor shortages, reduced sediment loads, and limited carbon absorption capacity, may hinder regional long-term sustainability, underscoring the need for integrated policies to address these challenges.

Dynamic evolution and multiple driving paths of urban-rural integration under symbiosis perspective: the case of the Yellow River Basin in China

The dilution factor (DF) quantifies the extent to which wastewater is diluted after being discharged into a receiving water body. It serves as a critical indicator for establishing effluent discharge standards and assessing aquatic ecological risks. Although extensive research has been conducted on river DF, limited attention has been paid to the rationality of DF calculation methods. Typically, the accumulated wastewater volume (AWV) within a catchment-rather than the wastewater volume in the nearby receiving river-is commonly used for DF calculation. During this process, the delineation of the sub-catchment plays a critical role in determining AWV. However, the impact of sub-catchment delineation on DF calculation remains unclear. This study utilizes a comprehensive dataset comprising streamflow records from 235 hydrological stations, effluent discharge data from 544 municipal wastewater treatment plants (WWTPs), and sub-catchment information within the Yellow River Basin to examine the influence of sub-catchment delineation on DF. The results revealed that when the sub-catchment area was less than 3 000 m2, there was no significant correlation between DF and streamflow. However, this correlation became pronounced when the sub-catchment area ranged between 3 000 and 5 000 m2. This trend may have primarily resulted from the higher spatial heterogeneity in the distribution of WWTP within smaller sub-catchments compared to that within larger ones. Such heterogeneity led to greater variability in AWV and consequently in the DF. As the sub-catchment area increased, the spatial geographic elements such as number of WWTPs became more spatially homogenized, and the spatial distribution of geographic elements such as WWTPs became more homogeneous, resulting in more stable AWV estimates. This spatial averaging effect highlights the correlation between DF and streamflow in larger sub-catchments. When sub-catchment boundaries were not defined, and wastewater discharge was assumed to flow throughout the entire river network in the Yellow River Basin, the resulting DF was significantly underestimated. Using such underestimated DF values as basis for regulatory decision-making may lead to overly stringent effluent discharge standards that do not reflect actual environmental capacity. Therefore, accurate delineation of sub-catchment boundaries is essential. It is recommended that pollutant transport models be used in combination with observed pollutant concentration data in the river to determine an appropriate sub-catchment boundary. Based on DF results that incorporated sub-catchment boundaries, the median DF values were 6 358.8 for the main stream and 28.5, 21.5, and 5.1 for third-, fourth-, and fifth-order tributaries, respectively. Additionally, the median DF values for rivers in the upper, middle, and lower reaches of catchment were 1 346.5, 9.3, and 48, respectively. Notably, temporal variation in DF was much smaller than spatial variation. These findings provide valuable insights for applying DF at the regional scale and for developing region-specific effluent discharge standards.

Addressing national goals for ecological conservation in the Yellow River Basin, this study focuses on its Henan segment (HYRB). We developed a VOR-SQ assessment framework by augmenting the classic Vitality–Organization–Resilience model with ecosystem services and an enhanced ecological quality indicator. Using multi-source remote sensing and statistical data, we examine the spatiotemporal evolution of ecosystem health in the HYRB from 2000 to 2020. The XGBoost-SHAP algorithm was applied to identify nonlinear drivers and threshold effects. Key findings indicate (1) a persistent “high west, low east” health gradient with an overall declining trend; western mountains remain healthy, while eastern plains, urban, and intensive agricultural areas show degradation. (2) Natural factors—evapotranspiration (ET), elevation, NDVI, and slope—dominate health dynamics, with critical thresholds (~1153 mm, ~457 m, ~0.76, ~10.5°, respectively) beyond which their impacts shift markedly. (3) Anthropogenic factors (GDP, population/road density) contribute less globally but cause strong local negative disturbances in plains. For instance, road density > 434 km/km2 or population density > 159 persons/km2 reverses their effects from positive to negative. Accordingly, we propose tailored strategies: western conservation, central farmland optimization, and eastern development control. By coupling the VOR-SQ framework with XGBoost-SHAP, this study offers a robust diagnostic tool for ecosystem health and adaptive governance in fragile socio-ecological systems.

Solanum rostratum is a globally regulated invasive species, known for its detrimental impacts on local biodiversity, human and livestock health, and agricultural productivity. This study employed the Biomod2 ensemble modeling framework to analyze the geographic distribution of S. rostratum in China, identify key environmental factors limiting its spread, and provide a scientific basis for its management and control. By integrating species distribution data with multiple environmental variables, we predicted the potential geographic distribution of this species. Pearson correlation analysis and variance inflation factor (VIF) testing were applied to identify significant environmental variables constraining its spread, including precipitation seasonality (bio15), mean temperature of the wettest quarter (bio8), precipitation of the warmest quarter (bio18), isothermality (bio3), precipitation of the driest month (bio14), and human footprint. Three Biomod2-based ensemble models (EMmean, EMca and EMwmean) were based on the receiver operating characteristic curve (ROC), true skill statistic (TSS), and Kappa coefficient. Of these, EMca demonstrated the highest predictive accuracy. The model identified highly suitable habitats for S. rostratum primarily in semi-arid and semi-humid regions with high human activity, including the Northeast Plain, bounded by the Greater Khingan, Lesser Khingan, and Changbai Mountains; the northern North China Plain extending to the Shandong Hills and Yellow River basin; and the Junggar Basin extending to the Altai Mountains. These regions should be prioritized for future monitoring and control efforts. This study provides both empirical data and theoretical insights to accurately delineate potential invasion zones of S. rostratum, enhancing surveillance and guiding effective prevention and control strategies.

Abstract Aiming at the seismic safety of hydraulic metal structures in the high-intensity seismic region of Northwest China, this study considers the spillway radial service gate of the Jishixia Hydropower Station in the Yellow River Basin as the research object. A dynamic timehistory analysis method was employed to numerically simulate the complex dynamic response under Intensity VIII seismic action. The results indicated the significant spatial distribution characteristics of the dynamic response. The peak displacement is concentrated in the central area of the top of the skin plate, and a significant stress concentration occurs in the mid-span areas of the main girder and radial arms, which are key components of the gate. A comparison with the static stress experimental results confirms that the peak dynamic response under a seismic load can reach 1.7 times the static experimental value. To enhance the seismic performance of the gate, structural optimization schemes involving local stiffening of the main girder and diagonal bracing of the radial arms were proposed without altering the existing structure. The simulation results show that, after optimization, the maximum displacement of the overall gate structure is reduced by 7.9%, and the amplitude of the dynamic stress at key parts of the gate is attenuated by more than 6.21%. This study provides a theoretical basis and technical support with significant engineering application value for safe design and performance improvement of gates in high-intensity seismic regions.

Under the background of the “dual carbon” strategy and regional coordinated development, the synergistic evolution of low-carbon logistics, regional economy, and ecological environment in the Yellow River Basin has become a key pathway to achieving high-quality development. Taking nine provinces (autonomous regions) within the basin as the study area, this paper constructed a coupling coordination evaluation index system for the LREES (Low-carbon Logistics–Regional Economy–Ecological Environment System), and measured the comprehensive development level of each subsystem using the entropy weight method. Based on the coupling coordination degree model, the temporal evolution of the three systems from 2010 to 2024 was systematically evaluated. In addition, global and local spatial autocorrelation models were introduced to identify spatial clustering patterns, while the obstacle degree model was used to identify key constraints at both the criterion and indicator levels. The results revealed that: the overall development level of the LREES systems steadily increased, with reduced regional disparities; the coupling coordination degree showed a trend of “fluctuating rise–gradual coordination,” with the average value increasing from 0.450 to 0.623, indicating continuously enhanced synergy; spatially, a gradient pattern of “downstream > midstream > upstream” emerged, accompanied by significant positive spatial autocorrelation; resource endowment and development scale were major constraints, while construction level, operational efficiency, and governance capacity were secondary. High-frequency obstacle indicators included per capita water resources, total import and export volume, and urban sewage treatment capacity. These findings offer theoretical support and policy guidance for promoting green transformation, enhancing system synergy, and advancing coordinated regional development in the Yellow River Basin.

The Gansu-Qinghai contiguous region of the upper Yellow River occupies a strategic position in China's ecological security framework. However, comprehensive long-term assessment of ecological quality changes and their mechanisms in this ecologically fragile zone remains limited. Systematically evaluating ecological quality dynamics is necessary for supporting high-quality development strategies in the Yellow River Basin. This study utilizes MODIS series remote sensing imagery from 2000 to 2022, accessed through the Google Earth Engine platform. The Remote Sensing Ecological Index (RSEI) was constructed via principal component analysis (PCA). Theil-Sen median trend analysis, Mann-Kendall tests, and coefficient of variation methods were applied to examine spatiotemporal patterns and stability. Pearson correlation analysis and random forest modeling were employed to quantify the contributions of ten driving factors. Results indicate that the ecological quality of the study area showed an overall improving trend with local fluctuations from 2000 to 2022. Spatially, it exhibited a west-high and east-low pattern, with "good" and "excellent" areas continuously expanding. About 43% of the region experienced ecological improvement, 20% showed degradation, and over 86% remained highly stable. Vegetation greenness was the dominant positive driver, while land surface temperature and dryness index had significant negative impacts. Precipitation and humidity displayed threshold responses, and socioeconomic factors such as GDP and population density mainly influenced local ecology through land-use intensity. Overall, ecological quality was jointly regulated by vegetation dynamics, hydrothermal conditions, and human activities. This study establishes baseline data for systematic ecological monitoring in high-altitude ecologically sensitive regions. The findings demonstrate that targeted ecological restoration projects have achieved measurable effectiveness, while emphasizing the necessity of integrating climate change considerations into future conservation management strategies for the upper Yellow River.

Driving mechanisms of vegetation carbon sink distribution based on explainable machine learning and evaluation of carbon sequestration in open-pit mines.

Pathways of driving mechanisms for ecosystem services in the Yellow River Basin: insights from scale prioritization and implications for differentiated ecological management.

A composite ecological drought index integrating multi-source water and heat stress with time-lag effects: Insights from the Yellow River Basin.

From climate knowledge to adaptive action: Crop water requirement and agricultural water risk in the Yellow River Basin