Concrete and sand materials exhibit significant nonlinear mechanical behavior during loading, where the non-stationary dynamic characteristics of stress-strain make it challenging for traditional prediction methods to achieve accuracy. To address this issue, this paper proposes a deep learning prediction model combining a Multi-head Attention-enhanced Gated Recurrent Unit (MUA-GRU) with a Non-Stationary Transformer. The model leverages self-attention mechanisms to capture the dynamic responses of materials during elastic, plastic, and failure stages, while integrating the KAN module to achieve efficient mapping of complex feature. Four sets of stress-strain data were generated using the PFC2D software based on the discrete element method(DEM), and the proposed model was validated through comparisons with Support Vector Regression (SVR), Long Short-Term Memory (LSTM), Informer, and CNN-BiLSTM-MA models. The Results show that the proposed model achieved a coefficient of determination (R²) of 0.987-0.996 for short- and long-sequence predictions, with the Mean Absolute Percentage Error (MAPE) as low as 0.65%, and a 20%-47% reduction in Mean Absolute Error (MAE) compared to the second-best model. The study indicates that the synergistic design of multi-scale feature extraction and non-stationary attention mechanisms significantly enhances the prediction accuracy of material mechanical properties,  providing a more reliable solution for predicting the mechanical behavior of complex materials and supporting related engineering applications.

With the acceleration of global climate change and urbanization, flood disasters occur frequently. Traditional flood control measures are insufficient to meet cities’ flood response needs, making it urgent to enhance urban flood resilience to improve disaster resistance and post-disaster recovery capabilities. Thirteen prefecture-level cities in the lower Yellow River basin were selected as the study area. Based on an improved Pressure-State-Response (PSR) framework, a four-dimensional resilience assessment system (Hazard-Exposure-Vulnerability-Adaptive Capacity, H-E-V-A) was constructed. The entropy weight-CRITIC combination weighting method was used to calculate indicator weights, and the Geodetector model was applied to analyze the driving factors of resilience spatial differentiation. The study found that from 2013 to 2023, the flood resilience index of the study area showed an overall fluctuating upward trend with a significant increase of 22.2%, indicating a marked improvement in resilience level. Spatially, resilience spread outward with Zhengzhou and Jinan as high-value centers; over time, the range of high-resilience cities expanded while the number of low-resilience cities decreased. Driving factor analysis indicated that total regional economic output, fiscal budget expenditure, medical and health service level, and information dissemination capacity were the main drivers, and the synergistic effect among these factors played a particularly significant role in enhancing resilience. Although the flood resilience of the study area has improved significantly over the past decade, regional differences persist. In the future, it is necessary to strengthen regional coordination and optimize urban layout to further enhance cities’ flood resistance capacity.

To investigate the relationship between new quality productive forces and carbon emission efficiency in the Yellow River Basin, and to provide theoretical support for achieving the carbon peaking and carbon neutrality goals and high-quality regional development, this study constructs evaluation index systems for both variables based on panel data from nine provinces (regions) in the Yellow River Basin from 2012 to 2023. A two-way fixed effects model and a mediation effect model are employed to measure and examine the relationship between new quality productive forces and carbon emission efficiency. The results show that: a) New quality productive forces exert a significantly positive effect on improving carbon emission efficiency in the Yellow River Basin, and this finding remains robust after multiple robustness tests.b) The development of new quality productive forces effectively enhances carbon emission efficiency through industrial structure upgrading and green technological innovation. c) The promoting effect of new quality productive forces on carbon emission efficiency is more pronounced in regions with lower economic levels, and is stronger in non-resource-based regions than in resource-based regions.Based on these findings, several policy recommendations are proposed, including continuously fostering new quality productive forces in the Yellow River Basin, optimizing the mechanisms of green technological innovation and industrial structure upgrading, and formulating differentiated development strategies tailored to local conditions.

To enhance the refinement, informatization, and modernization of reservoir operation and management, and to provide practical references for the construction of the digital twin water conservancy system, this paper takes Guxian Reservoir as a case study to explore key technologies and applications for digital twin platform construction. Relying on integrated space-air-ground-water-engineering sensing technology, a data foundation driven by multi-source data fusion has been established. Based on a one-dimensional-two-dimensional coupled hydrodynamic mechanism model characterized by time-varying parameters, and combined with the self-developed “Zhihe Shijie” twin engine, a multi-scale coupled model is constructed. This model covers impoundment inundation, disaster assessment, and visual simulation. The Guxian Reservoir Digital Twin Platform has played a critical role in flood control operations. It supports the “Four Pre” functions of reservoir management, realizing the dynamic simulation and visualization of flood regulation, evolution, and disaster assessment. This effectively improves decision-making capabilities for flood control. Furthermore, it provides a pilot paradigm for the construction of the Digital Twin Yellow River. Its development experience serves as a reference for other water conservancy projects, while its core technologies and multi-scenario application modules support the interconnection, collaborative development, and sharing of the “2+N” business system of the Digital Twin Yellow River.

In response to the local flow field changes caused by the layout of bottom-mounted continuous underwater structures, the RNG k-ε turbulence model is used to analyze the sediment erosion and deposition patterns caused by bottom-mounted continuous structures. The results show that when the structure can cross the water longitudinally, a peach-shaped vortex will be formed behind the backflow side, and a scouring pit will be formed at the side heading point, and the depth of the scouring pit is negatively correlated with the length of the structure. Due to the water-blocking effect of the structure, eddies will be formed on the frontal and backcurrent sides of the structure, and when the structure is wide, eddies will be formed on the upper side and siltation, and the amount of sedimentation is positively correlated with the width of the structure. Because the structure and the water flow direction are at a certain angle, the flow velocity difference is formed in the same longitudinal section, and the water flow flows from the obtuse angle on the back flow side to the acute angle, and forms an arc-shaped vortex at the acute angle, and the vortex direction is towards the lower side of the structure, which has a certain threat to the stability of the lower side of the structure.

In order to explore the intrinsic link between digital economy development and industrial water use efficiency in the Yellow River Basin, based on the panel data of 55 cities in the Yellow River Basin from 2013 to 2022, the Super-SBM model with non-expected output is applied to measure the industrial water use efficiency of the cities in the Yellow River Basin, the entropy method is used to measure the level of digital economy development, and the fixed effect model is constructed to empirically Analyze the influence effect of digital economy development on industrial water use efficiency. The results show that a) the digital economy significantly improves the industrial water resources utilization efficiency, and further releases the improvement effect under the role of industrial structure upgrading. b)The digital economy has an obvious effect on the improvement of industrial water resources utilization efficiency in non-resource cities and the humid and semi-humid ecological zones of the northeastern part of the country. c)The development of the digital economy has a significant spatial spillover effect, which is able to improve the industrial water resources utilization efficiency of the neighboring cities. Therefore, it is necessary to strengthen the construction of the digital economy, establish a modernized industrial system, and give full play to the positive effects of the digital economy on water resources utilization according to local conditions.

The implementation of gully consolidation and highland protection projects in the Loess Plateau Gully Region plays a significant role in safeguarding national land security, food security, ecological security, and livelihood security. This study aims to deepen and expand the theoretical research on such projects and provide references for their practice. Based on field surveys of 71 projects in Gansu and reviews of their engineering design documents, we conducted statistics, induction, and analysis on investment, construction content, protection targets, configuration modes, and functions of the measures. The results indicated the following: a) The measures could be categorized into 10 types: gully head landfill, drainage diversion into channels, detention ponds, gully head protection, land consolidation, slope masonry protection, willow check dams, forest and grass restoration, temporary measures, and other measures. b) The average investment per project was 1.215 5 million yuan, with projects under 2.5 million yuan accounting for 94%. The investment for the 10 types of measures ranged from 0.008 1 to 1.131 3 million yuan per project. c) Comprehensive analysis of investment proportion, adoption rate, and function revealed that among the 10 types, gully head landfill and drainage diversion into channels were the core measures, while detention ponds, gully head protection, and forest and grass restoration were important measures. d) The key protection targets of the completed projects were roads at various levels on the tableland, urban residential areas, villages, and prime farmland. The comprehensive “Interception-Storage-Drainage-Consolidation” treatment system, centered on controlling tableland runoff and constructed jointly by various measures, has yielded significant ecological, economic, and social benefits. e) The task of gully consolidation and highland protection remains arduous, and the construction scale of such projects should be further expanded.

The implementation of the major national strategy for ecological conservation and high-quality development in the Yellow River Basin urgently necessitates the synergistic advancement of environmental protection and industrial growth. Practical experiences from representative river basins both domestically and internationally can provide valuable insights for promoting such coordination in the Yellow River Basin. Through a comparative multi-case analysis approach, this study selects the Mississippi River, Rhine River, Amazon River, Nile River, Yangtze River, and Pearl River as reference cases to examine the commonalities and differences between the Yellow River Basin and these basins in terms of harmonizing environmental protection with industrial development. Building on the diversified development experiences of these reference basins, as well as considering the unique characteristics and challenges of the Yellow River Basin, strategies are proposed to further advance the synergistic development of environmental protection and industry. The comparative analysis reveals that while all reference basins emphasize the importance of policy and regulatory guidance, scientific and technological innovation, and the establishment of digital-intelligent monitoring systems, the Yellow River Basin exhibits significant deficiencies in these areas. Moreover, it faces distinct challenges such as severe water scarcity, a single industrial system, and a high proportion of water-intensive industries. To further promote the synergistic development of environmental protection and industry in the Yellow River Basin, the following strategies are recommended: improving vertical and horizontal coordination and compensation mechanisms for ecological conservation; adhering to ecological priority and technological innovation to drive green development; leveraging big data resources to lead the digital-intelligent transformation of industrial development in the basin; and promoting the efficient growth of green industries to establish a green, low-carbon, and circular economic system.

When we using two-dimensional hydrodynamic models for the simulation of flood evolution caused by dam-break, there exists no systematic investigation into the causes of computational deviations arising from differences in grid resolution. The author clarified the reasons why the grid size affects the model results, identified the conditions that require consideration of the grid size, and indicated the necessity of considering the grid size in the simulation of dam-break floods. By establishing numerical models of plain reservoir breach floods with different flood levels and grid sizes, two main processes of how grid size affects the model calculation results are proposed, and corresponding recommended optimization methods for simulating dam breach flood grid sizes are proposed.

In order to promote the high-quality development of the National Water Network, this study systematically reviewed the historical evolution patterns of water network construction and explored future optimization paths. Based on an analysis of key historical nodes, the development of the water network was divided into five stages: the initial exploration and foundation-laying period, the rapid development period of backbone projects, the rapid development and key breakthrough period, the exploration period of comprehensive water management and sustainable development, and the proposal and systematic promotion period of the national water network strategy. This division revealed the evolutionary pattern of the water network from single-project constructions to a complex system of “framework-network-node”. The results indicate that water network construction has achieved significant progress in water management concepts, engineering synergy, and systemic support. However, it still faces challenges, including increased vulnerability exacerbated by climate change, insufficient multi-objective coordination, prominent cumulative ecological effects, bottlenecks in smart regulation technologies, and imperfect cross-regional governance mechanisms. In the future, the high-quality construction of the water network should be advanced by optimizing spatial layout planning, making breakthroughs in key technologies, implementing ecological concepts, promoting smart regulation, and improving institutional mechanisms, thereby ultimately enhancing the guarantee capacity of water resources.

Vegetation concrete is widely used in high and steep slope protection, rocky slope protection, and riparian hydraulic engineering protection due to its dual advantages of structural strength and vegetation performance. In practical applications, it is crucial to synergistically optimize its mechanical strength, pore structure, alkalinity environment for plant growth, and durability. To deepen the integration of pore structures and ecological functions of vegetation concrete, and to provide references for improving its application, this paper systematically reviews the research achievements regarding its performance and engineering applications. On this basis, an application workflow for vegetation concrete is proposed, and the main challenges and corresponding solutions for its performance optimization are identified as follows: a) The contradiction between strength and porosity: Increasing porosity benefits plant growth but significantly reduces structural strength. The solutions include optimizing aggregate gradation and binder proportions, adding fibers to improve pore-forming quality and strength, and developing intelligent regulation technologies for pore structures. b) The short duration and high cost of existing alkali-reduction technologies: The proposed solutions involve developing pH-sensitive materials, regulators, and low-alkali paste materials; utilizing microbial mineralization for alkali fixation; strengthening post-maintenance and monitoring; and implementing dynamic alkali reduction. c) Inherent deficiency in durability: Vegetation concrete is vulnerable to damage under freeze-thaw cycles and chemical erosion, resulting in a short service life, especially in alpine and cold regions. The solutions focus on new material development and pore structure optimization, such as applying geopolymers and composite microorganisms, developing anti-freeze-thaw additives and slow-release nutritional mineral admixtures, and constructing pore structures that prevent freeze-thaw damage while facilitating plant root growth.

Spartina alterniflora, as an invasive alien species, poses a serious threat to the ecological environment and biodiversity of the coastal wetlands of the Yellow River Delta. In this study, the spatial distribution, vegetation coverage and phenological characteristics of Sparnia alterniflora were monitored and analyzed based on satellite remote sensing data from 2017-2023 in the Yellow River Delta. The results showed that after mowing and ploughing, the overall NDVI within the Spartina alterniflora coverage declined. After the first mowing, the recurrence of spartacola alterniflora was more serious in the south bank with dense distribution of tidal gully, while the treatment effect of the flat tidal flat on the north bank was better. However, after multiple mowing and ploughing, spartacola alterniflora could be basically removed, and only a small scale recurrence was found near the tidal gully.Mowing and ploughing initiated before the Spartina alterniflora reaches its seasonal growth peak is more effective than carrying out the treatment during the peak-growing period. During the treatment period, Spartina alternia gradually spread outward with the sedimentation of sediment to the sea near the mouth gate. 

The low irrigation water use efficiency in China significantly constrains the sustainable and high-quality development of agriculture. To accurately identify issues in water-saving agricultural development, it is essential to simulate the evolution of irrigation water use efficiency under the synergistic effects of multiple driving factors, starting from an analysis of the driving mechanisms. For this purpose, this study took the Hetao Irrigation District as a case study. After identifying the key driving factors, we integrated socio-hydrology principles and system dynamics methodology to develop an evolution model of irrigation water use efficiency for the irrigation district. The model was used to simulate its historical evolution and future development trends under different scenarios. Model validation demonstrates its effectiveness in capturing the feedback relationships among variables within the system. Simulation results indicate that the medium development scenario presents the most desirable development path for the irrigation district. By 2030, the proportion of water-saving irrigated area is projected to reach 99.23%, irrigation water use efficiency is expected to improve to 0.416, while irrigation water withdrawal will decrease to 4.369 3 billion m³   (a reduction of 2.69% compared to 2018). The study confirms the validity of the constructed model and suggests that the medium scenario is more conducive to enhancing irrigation water use efficiency and promoting the ongoing development of water-saving agriculture in the Hetao Irrigation District.

Soil erodibility factor (K) has become a crucial parameter for dynamic monitoring of soil erosion, estimation of soil loss, and evaluation of soil and water conservation effectiveness in China. Localizing the calculation method of K values is beneficial to improving the accuracy of dynamic soil erosion monitoring. Taking Xifeng District of Qingyang City, located in the core area of the Dongzhi Tableland, as the study area, this research calculated the K values in the loess tableland and gully region based on in-situ measured data from 35 sampling points, combined with the EPIC model and Zhang Keli’s modified formula. The Optimal Parameter-based Geographical Detector (OPGD) was adopted to analyze the main influencing factors of soil erodibility. The results show that: a) The K values in the loess tableland and gully region range from 0.015 2 to 0.017 8 t·hm²·h/(MJ·mm·hm²). Spatially, the high-K zones (K≥0.016 8) in the study area are concentrated in gully areas and residual tablelands surrounded by gully heads, showing an irregular strip-like distribution, while the low-K zones (K<0.016 8) are clustered in regions with large and flat tableland surfaces. b) Soil erodibility in the loess tableland and gully region is affected by multiple factors, and the interactive effects among these factors are significantly stronger than the individual effects of single factors. Among various influencing factors, soil physicochemical properties, especially sand content and organic carbon content, are the dominant factors affecting soil erodibility.

The Ten Tributaries, being a network of ten primary tributaries in the upper reaches of the Yellow River, are characterized by a fragile ecosystem, severe composite erosion, and pronounced spatial heterogeneity of environmental elements. The establishment of a spatial zoning framework for ecological restoration is therefore a critical foundational measure to enhance the systematic nature and holistic efficacy of restoration efforts in this region. Drawing upon multiple field investigations and in-depth analyses, combined with a comprehensive review of existing literature, this paper identifies the prominent challenges in the current ecological governance of the Ten Tributaries and proposes key research questions and future directions for developing a scientifically-grounded spatial zoning strategy for ecological restoration. The findings reveal that despite years of management, which have led to some environmental improvements, significant issues persist, including a lack of systematic governance, the application of monolithic restoration measures, insufficient adoption of new technologies, and the absence of a scientifically-grounded spatial zoning plan for ecological restoration. The critical scientific questions that urgently require resolution include the spatiotemporal distribution patterns and mechanisms of wind-water composite erosion;the spatial heterogeneity characteristics of ecological functions; the multi-phase composite sediment and hyperconcentrated flood transport processes and the spatial distribution characteristics of high-sediment flood sources;the identification of spatial suitability for ecological restoration through forestry and grassland vegetation; and the development of spatial zoning methods for ecological restoration of the Ten Tributaries based on multi-objective synergy. Consequently, this study advocates for a new approach that proceeds from the distinct spatial heterogeneity of the region’s ecological elements. Guided by the technical principle of multi-scale and multi-dimensional coupling between landscape patterns and ecological processes, this approach aims to identify priority areas for ecological protection and restoration in the Ten Tributaries. By implementing targeted, site-specific measures based on ecological suitability distribution patterns, the goal is to advance a systematic, holistic, and comprehensive spatial ecological restoration of the Ten Tributaries. Such efforts are of great significance for establishing a robust ecological security barrier in the Yellow River Basin.

Abstract: As global temperatures continue to rise and extreme weather events occur with increasing frequency, climate change has become an urgent global challenge. Against the backdrop of the shift of global climate governance toward an “implementation-oriented” phase, this study explores synergistic mechanisms between energy transition pathways and watershed ecological governance, drawing on thematic presentations from the China Pavilion side event at the 30th Conference of the Parties to the United Nations Framework Convention on Climate Change (COP30) and practical experience in watershed ecological management. The findings indicate that climate change has intensified the dual challenges of global energy security and watershed ecosystem sustainability, making the coordinated advancement of energy transition and ecological governance a core pathway for achieving green and low-carbon development and ensuring ecological security. Reducing energy consumption represents the most economically viable option for energy transition, while multi-energy complementarity provides an innovative direction for watershed-level energy transformation. As a mature renewable energy source, hydropower plays a significant role in peak regulation and in maintaining the stability of power supply. This role is particularly prominent in the Yellow River Basin, characterized by “low water and high sediment,” where existing and planned hydraulic projects exert substantial influence on basin-wide water-sediment regulation. Under current conditions of reduced sediment inflow, hydropower generation, ecological protection, and optimized water resources allocation can deliver even greater benefits. Using turbulence research as an example, a velocity distribution formula derived from the turbulent eddy model demonstrates cross-disciplinary applicability in fields such as hydraulic engineering, aeolian sand control, and energy efficiency optimization in aero-engines, underscoring the critical role of fundamental scientific breakthroughs in supporting applied research and technological implementation. The objectives of energy transition and watershed ecological governance are inherently aligned, and the eco-economy emerging from their integration can leverage capital mechanisms to achieve a win-win outcome between ecological protection and economic development. Finally, the study emphasizes that successful energy transition requires the establishment of a full-chain collaborative system spanning from fundamental research to integrated governance, strengthening innovation at the source, activating energy efficiency markets, and ensuring policy support to drive a broader transformation of the development paradigm.

To assess the green development effect of new quality productivity and explore its path to promoting the high-quality economic development of cities in the Yellow River Basin, based on the panel data of 77 prefecture-level cities in the Yellow River Basin from 2011 to 2021, the entropy Weight-TOPSIS method was used to measure the development level of new quality productivity. A Spatial Durbin Model was constructed to empirically analyze the promoting effect of new quality productivity on the high-quality economic development of cities and its spatial spillover effect. A mechanism test model was constructed to explore the transmission mechanism of new quality productivity promoting the high-quality economic development of cities. The results show that: a) During the research period, the development of new quality productivity in each city in the Yellow River Basin not only promoted the high-quality economic development of the city itself, but also had a significant spatial spillover effect on the high-quality economic development of neighboring cities. b) The development of new quality productivity promotes the high-quality economic development of cities in the Yellow River Basin through intermediary channels such as environmental regulation, energy conservation and the upgrading of industrial structure. c) The direct and indirect effects of new quality productivity promoting the high-quality economic development of cities are the strongest in downstream cities, followed by middle reaches cities, and the weakest in upstream cities. Suggestions: Optimize and improve the top-level design for the development of new quality productivity, give full play to the synergy between new quality productivity and the “dual carbon” goals, strengthen the research and development of core technologies such as 5G networks, the lnternet of things, and artificial intelligence, and enhance the development momentum of new quality productivity.

To broaden the research horizon of how the digital economy empowers low-carbon development and to inform decision-making for ecological protection and high-quality growth in the Yellow River Basin, this study constructs an indicator system and quantifies the digital-economy development level by using panel data of the nine basin provinces from 2012 to 2022. On this basis, we specify a benchmark econometric model in which carbon-lock-in intensity is the explained variable and digital-economy development the core explanatory variable, treat industrial-structure upgrading as the mediating variable and urbanisation as the moderating variable, and further build mediation and moderation-effect models to empirically identify the carbon-unlocking effect of the digital economy and its underlying mechanisms.The findings indicate: a) The development of the digital economy in the Yellow River Basin exhibits a robust carbon-unlocking effect; the effect is markedly stronger in the middle-lower reaches, in areas hosting innovation-oriented industrial clusters, and in regions where resource-intensive industries account for a smaller share of output. b) The digital-economy development delivers its carbon-unlocking impact by propelling industrial-structure upgrading, which significantly and positively mediates the Basin-wide effect. c) during the sample period, urbanization negatively moderates the carbon-unlocking effect of the digital economy in the Yellow River Basin.Policy implications: a) Accelerate digital-economy expansion to reinforce its carbon-unlocking capacity. b) Implement region-specific strategies that coordinate digital-economy growth with green low-carbon industries across the Yellow River Basin. c) Further optimize the industrial structure to promote green low-carbon sectors. d) Pursue green urbanization to create low-carbon living spaces.

The problem of distortion in remote sensing vegetation indices due to terrain effects is more prominent in the hilly and loess plateau areas with intense terrain changes. To obtain the true information about vegetation growth, it is necessary to eliminate the terrain effects in remote sensing images and perform terrain correction. Taking the complete ratio-type, non-complete ratio-type, and non-ratio-type vegetation indices (NDVI, EVI, GVI) in the loess hilly area as the research objects, the SCS+C correction model was used to perform terrain correction for the terrain effects caused by the local solar incidence angle, the spectral variations of the same land type caused by the terrain effects, and the abnormality of vegetation indices caused by the aspect. The improvement effect of terrain correction on the three vegetation indices was investigated, and the correlations between the terrain correctioned vegetation indices and terrain factors (elevation, slope, aspect, etc.) and the measured leaf area index were analyzed. The results show: a) Among the three vegetation indices, GVI is less affected by terrain effects, while EVI and NDVI are relatively more affected by terrain effects. When using EVI and NDVI in related studies, terrain correction must be performed. b) After terrain correction, the regularity of the three vegetation indices changing with terrain factors and the correlation with the measured leaf area index have both been enhanced. c) Using the SCS+C correction model for terrain correction is feasible and effective. The terrain correction effect of the three vegetation indices is as follows: EVI > NDVI > GVI.

To explore the coupling and coordination status and mutual response relationship between digital economy and green development in the Yellow River Basin, and to provide references for ecological protection and green high-quality development in the basin, based on the analysis of the coupling mechanism between digital economy and green development, this paper uses panel data of 64 prefecture-level cities (prefectures) in the Yellow River Basin from 2013 to 2022. The entropy weight method is adopted to measure the development level of digital economy, the Super-efficiency-SBM model is used to measure the efficiency of green development, and the coupling coordination degree model is employed to measure the coupling and coordination status between digital economy and green development. The PVAR model is used to empirically analyze the mutual response relationship between digital economy and green development. The research shows that: a)The development level of digital economy in the Yellow River Basin has steadily increased, but it is still at a relatively low level at the end of the study period. Spatially, it shows the highest level in the downstream region, followed by the middle reaches, and the lowest in the upper reaches, with a circular structure centered on relatively high provincial capital cities. b)The efficiency of green development in the Yellow River Basin has also steadily increased during the study period, but the imbalance in green development among prefecture-level cities is prominent. c) The coupling and coordination level between digital economy and green development in the Yellow River Basin has been increasing year by year, rising from a barely coordinated level at the beginning of the study period to a primary coordinated level at the end. Spatially, the downstream region has the highest level, followed by the upper reaches. d)Both digital economy and green development have strong self-dependency, and a two-way high-quality interaction relationship has not yet been formed between them. The promoting effect of digital economy on green development is relatively strong, but the promoting effect of green development on digital economy is relatively weak. Suggestions: Accelerate the construction of new digital infrastructure in the Yellow River Basin to further improve the development level of digital economy; formulate plans and strengthen cross-regional cooperation to quickly narrow the regional gap in green development; promote the further improvement of the coupling and coordination level between digital economy and green development through reasonable industrial layout and technological innovation.

The Yellow River Basin is the region in China that suffers from the most severe soil and water loss and has the most fragile ecological environment. The water and soil conservation measures in the Yellow River basin have significant ecological, economic and social effects. To provide theoretical support for effectively enhancing the functional value of soil and water conservation, realizing its exchange value, and amplifying its financial value, and to offer references for accelerating the formation of a pattern for realizing the value of ecological products in soil and water conservation in the Yellow River Basin and promoting the high-quality development of soil and water conservation in the Yellow River Basin, this study, from the perspective of sustainable development, reveals three value forms of soil and water conservation effects, namely: ecological products that embody functional value, ecological commodities that embody exchange value, and ecological financial products that embody financial value. Furthermore, it clarifies the value conversion process of soil and water conservation effects through four stages: valorization, productization, commercialization, and financialization. It also expounds on five mechanisms of value transformation, including clarification of property rights, value accounting, value pricing, market absorption, and financial innovation. Finally, it puts forward countermeasures to improve the value transformation mechanism, such as establishing the common ownership of water resources in the basin, optimizing the value accounting model and methods for soil and water conservation, and implementing a differentiated value pricing mechanism.

Urbanization has been accompanied by rapid growth in population, energy consumption, and carbon emissions. To forecast the peak of energy-related carbon emissions in the Yellow River Basin under urbanization and provide a reference for advancing ecological conservation and high-quality development in the basin, this study calculates energy-related carbon emissions based on energy consumption data of eight major energy types across provinces (regions) in the Yellow River Basin from 2000 to 2021. The LMDI model is employed to decompose the factors influencing energy-related carbon emissions in the basin, while an extended STIRPAT model is used to forecast peak energy-related carbon emissions under multiple scenarios (business-as-usual, energy-saving, low-carbon, and high-energy-consumption). The results indicate that: 1) From 2000 to 2021, total energy carbon emissions in the Yellow River Basin continued to grow, but at a declining rate. Economic development, urbanization, and population growth promoted energy carbon emissions, while optimization of energy structure, energy intensity, and industrial structure suppressed them. Economic development was the primary driver of emission growth, whereas energy intensity was the main factor suppressing emissions. 2) Under the current, energy-saving, and low-carbon development models, the peak range for energy-related carbon emissions in the Yellow River Basin is estimated to be between 1.80 and 1.87 billion tons, with the peak occurring between 2030 and 2035. In contrast, under a high-energy-consumption development model, the peak is unlikely to occur before 2040. 3) Regulating carbon emission intensity helps reduce peak energy carbon emissions in the Yellow River Basin, while optimizing the energy structure and improving energy efficiency can facilitate an earlier peak. Recommendations include optimizing urban planning, promoting industrial structure upgrades, strengthening public education on low-carbon awareness, advocating low-carbon lifestyles, expanding renewable energy adoption, and optimizing the energy consumption structure.

This study prepared glass-ceramics using Yellow River sediment as the primary raw material. Combined with performance testing methods such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), fourier-transform infrared spectroscopy (FTIR), and hardness testing. The results demonstrate that: The main crystalline phase precipitated in the glass-ceramics made from Yellow River sediment is ferrite silicate. Crystallization begins inside the particles and gradually extends to the exterior. The primary influencing factors for the flexural strength, vickers hardness, bulk density, acid resistance, alkali resistance, and thermal properties of the glass-ceramics are crystallization time, nucleation time, crystallization time, nucleation temperature, crystallization temperature, and nucleation time, respectively. The optimal nucleation and crystallization regime is nucleation temperature 750 ℃ (60 min) and crystallization temperature 910 ℃ (180 min). The glass-ceramics made from Yellow River sediment has a flexural strength of 79.07 MPa, young's modulus of 51.59 GPa, vickers hardness of 6.37 GPa, and fracture toughness of 1.39 MPa·m^1/2. These properties comply with the “Glass-ceramics for Architectural Decoration” standard. Under nucleation temperature 720 ℃ (60 min) and crystallization temperature 880 ℃ (180 min), the dielectric constant and dielectric loss of the microcrystalline glass made from Yellow River sediment are 7.43 and 0.88, respectively. These values meet the performance requirements of the “Structural Ceramic Materials for Electronic Components” standard.

The “Ji Bend” of the Yellow River region is renowned as an important “energy granary” in northern China. In the context of the “dual carbon” goals, it faces the challenge of reducing emissions from traditional high-energy-consuming industries and transitioning its resource-based economy. This necessitates the promotion of green and low-carbon development through technological innovation. To provide insights for ecological protection and high-quality development in this region and the entire Yellow River basin, this study focuses on 15 prefecture-level cities in the “Ji Bend” of the Yellow River, with a research period from 2012 to 2022. Using an optimized four-stage SBM-DEA model, the low-carbon innovation efficiency of each city is calculated. The study also explores the spatio-temporal differences in low-carbon innovation efficiency among these cities using methods such as the Dagum Gini coefficient, standard deviation ellipse, and gravity model, along with σ-convergence and β-convergence tests. The results show that: a) From 2012 to 2022, the overall low-carbon innovation efficiency of the cities in the “Ji Bend” of the Yellow River remained low, with N-shaped fluctuations. Only Zhongwei and Taiyuan achieved DEA efficiency, while other cities did not; b) There is limited collaborative cooperation in low-carbon innovation among the cities, and the level of regional integration is low, leading to a phenomenon of “individual efforts” in low-carbon innovation; c) The spatial distribution of low-carbon innovation efficiency in the “Ji Bend” cities roughly follows a “higher in the south, lower in the north” pattern, with polarization between the cities. A “catch-up” effect exists, and by the end of the research period, the number of high-efficiency cities increased, though significant differences still remain between the cities; d) Improvements in education levels have a significant positive impact on the low-carbon innovation efficiency of the cities, whereas higher economic development levels and urbanization rates have a suppressive effect on this efficiency. Recommendations are made to address the issues in low-carbon innovation in the cities of the “Ji Bend”.

Research on the spatiotemporal changes in carbon storage is an important prerequisite for achieving regional low-carbon, high-quality development based on the “dual carbon” goals. This study employs a method combining supervised classification with field surveys to extract land use information of Bayannur City using high-resolution satellite imagery data. The study quantifies the spatiotemporal changes in carbon storage in Bayannur City from 2015 to 2021 based on the InVEST model. The results show that: a) Carbon storage in Bayannur City increased by a total of 97.55 million tons from 2015 to 2021, with high-value areas concentrated in Dengkou District, Hangjin District, Linhe District, and Wuyuan District, and low-value areas concentrated in Urad Front Banner District and Urad Middle Banner District. b) Changes in land use are consistent with changes in carbon storage. Compared to 2015, cultivated land and grassland areas in Bayannur City increased significantly by 1 740.00 km² and 11 099.09 km², respectively, while unused land decreased by 13 143.96 km². The area of water bodies showed an initial increase followed by a decrease over the six years. Significant changes were observed in the conversion of unused land to grassland in Urad Rear Banner and Urad Middle Banner, resulting in carbon storage increases of 36.72 million tons and 58.70 million tons, respectively.

New quality productive forces are the core driving force for the construction of a modern industrial system. To provide references for the deep transformation and upgrading of industries in the Yellow River Basin and the construction of a modern industrial system, this paper analyzes how new quality productive forces enable the deep transformation and upgrading of traditional industries in the Yellow River Basin towards high-end, intelligent, and green development. It also examines the internal logic of how disruptive and frontier technological innovations empower emerging and future industries. Based on the current development status of the Yellow River Basin, this paper identifies issues in the empowerment process of new quality productive forces, such as weak technological innovation foundations, insufficient supply of high-quality labor, high pressure for green transformation, insufficient vitality of data elements, and imperfect new forms of production relationships. Therefore, this paper proposes practical pathways to strengthen the empowerment of new quality productive forces in the Yellow River Basin’s modern industrial system, including strengthening the cultivation of high-quality labor, reinforcing technological support, facilitating the flow of data elements, accelerating green and low-carbon transformation, and deepening institutional and mechanism reforms.

To provide insights for accelerating the development of new productive forces in the Yellow River Basin, based on an analysis of the internal mechanisms driving the development of new productive forces, an evaluation index system for new productive forces is constructed from three dimensions: laborers, labor objects, and means of labor. Using panel data from nine provinces in the basin, the vertical and horizontal range method is employed to measure the development level of new productive forces from 2012 to 2022, analyzes regional imbalance with Kernel density estimation and Theil index, and examines spatial patterns and correlation via Moran’s Index and ArcGIS. The result show that: a) The overall level is low but exhibits a good upward trend, with growth across all nine regions. b) Significant disparities exist: Shandong ranks highest, followed by Sichuan and Shaanxi, while Qinghai and Gansu are relatively low; downstream regions outperform the middle reaches, which in turn surpass the upstream. c) Spatial differences are mainly reflected in the gap between upstream and mid-downstream areas, and within the upstream, Sichuan differs greatly from others, with obvious polarization remaining by the end of the study period. d) There is significant positive spatial correlation, with a pattern of “higher in the east and lower in the west” and “higher in the south and lower in the north”. Shandong, Henan and Shaanxi are high-high clusters; Shanxi and Inner Mongolia are low-high clusters; Gansu, Ningxia and Qinghai are low-low clusters; Sichuan is a high-low cluster. The following recommendations are proposed: Adapting to local conditions to leverage strength and address weakness; Promoting regional linkage and coordinated development; Achievement transformation; And advancing industrial upgrading to create more opportunities for new productive forces.

The upper reaches of the Yellow River (UPYR) serve as the primary source area for the basin’s runoff. It is essential to quantify the impacts of climate change and anthropogenic activities on the variation patterns of runoff in this region to enhance effective water resource management and support informed decision-making within the Yellow River Basin. In this study, we developed the SWAT hydrological model for the upper reaches of the Yellow River, calibrating and validating it from the base period of 1964 to 1980. We systematically evaluated the effects of climate change and human activities—including water usage, reservoir regulation, and land use—on runoff changes from 1981 to 2020. The findings indicate that a) The basin is currently undergoing a significant increase in both precipitation and temperature, with precipitation levels rising at a rate of 8.11 mm per decade and a corresponding warming rate of 0.35 ℃ per decade. It is important to note that there is spatial heterogeneity in the intensity of the impacts of climate change. In the source area, the contribution rate of the Jimai climate factor is 94%. In contrast, in the headway region, the contribution rate decreases to 21%. b) The influence of human activities on runoff attenuation exhibits spatial gradient characteristics, with variations ranging from 60% to 80% between Lanzhou and Toudaoguai. Human water consumption is identified as the principal contributing factor, accounting for approximately 40% to 45% of this phenomenon. The establishment and operation of the reservoir have resulted in a temporal redistribution of runoff, leading to a decrease of 18.11% ± 6.27% during the flood season and an increase of 12.33% ± 4.2% during the non-flood season. c) Between 1964 and 2020, the annual runoff in the upstream region of the Yellow River experienced a decline of 148 million cubic meters per decade. An analysis of the factors contributing to runoff reveals that precipitation recharge is the primary determinant, accounting for approximately 80% ± 11.33%. This is followed by contributions from snow and ice melt, thawing of frozen soil, and groundwater recharge. The findings of this study elucidate the nonlinear superposition effects of climate change and anthropogenic activities in the upper reaches of the Yellow River, thereby providing theoretical support for understanding the variations in upstream runoff in the context of climate change.