Since its implementation, the 1987 Yellow River Water Allocation Scheme has strongly underpinned water resources management in the Yellow River Basin and played a significant role. Currently, marked changes have occurred in the basin’s water-sediment regime, engineering conditions, and socioeconomic development pattern, making the adjustment of the Yellow River water allocation scheme a matter of widespread concern. This paper summarizes theories and methods supporting the adjustment of the Yellow River water allocation scheme: the mechanism of watershed healthy water balance based on the Budyko Equation for human societal water use, the theory of watershed equitable allocation of water resources, and the model of incremental equitable allocation. It proposes key research findings focused on optimizing the relationship between in-stream and off-stream water uses and scientifically adjusting the allocation of off-stream water used among provinces, thereby supporting the formulation, approval, and implementation of an adjusted 1987 Scheme. The adjustment of the 1987 Scheme represents a spatial redistribution of water resources in the Yellow River Basin. It can alleviate the existing rigid water shortages in the six upstream and midstream provinces. To fundamentally address water scarcity in the Yellow River Basin, it is imperative to accelerate the implementation of the water diversion project from other basins to improve the supporting capability of the basin’s water resources.

In order to provide a reference for resolving the problems of resource curse and ecological constraints in resource-based cities in the Yellow River Basin and promoting the sustainable development of the basin, an index evaluation system covering three dimensions of new quality laborers, new quality labor objects, and new quality labor materials was constructed. The entropy weight-TOPSIS method was used to assess the new quality productive forces development level of 34 resource-based cities in the Yellow River Basin from 2012 to 2023. The spatial-temporal evolution pattern of the new quality productive forces level was measured using kernel density estimation and the grey prediction GM(1,1) model. The obstacle degree model was used to analyze the influencing factors of the new quality productivity level. The results show that: a) Among the resource-based cities in the Yellow River Basin, the number of cities in the rapid growth type is the largest, and the average level of new quality productivity shows an inverted V-shaped growth trend. b) The development of new quality productive forces in these cities tends to converge, and the forecasted average index from 2024 to 2028 demonstrates a stable upward trajectory. c) The top five obstacle factors affecting the development of new quality productivity are the growth rate of broadband access users, the density of road lines, the proportion of fiscal science and technology expenditure, the ratio of R&D personnel to employed personnel, and the intensity of waste gas emissions.

Scientifically estimating urban carbon emissions and identifying their influencing factors is fundamental to formulating regional pollution reduction and carbon reduction strategies. To enrich research on urban-scale carbon emissions and provide a reference for the green and low-carbon development of the economy and society in Northwest China, this study used 37 prefecture-level cities (prefectures) in four provinces (regions) (Shaanxi, Gansu, Ningxia, and Qinghai) of Northwest China as sample units. Based on nighttime light data, the carbon emissions of each prefecture-level city from 2012 to 2022 were estimated, and their spatiotemporal patterns were analyzed. A spatial econometric model was constructed, and the influencing factors of carbon emissions were analyzed based on panel data from the four provinces (regions). The results show that: a) Carbon emissions in Northwest China generally showed an increasing trend during the study period, with Shaanxi showing the largest base and the largest increase in carbon emissions, while carbon emissions in Qinghai were relatively low and showing a decreasing trend. b) Carbon emissions varied greatly among provinces (regions) and prefecture-level cities (prefectures) in Northwest China. During the study period, the total carbon emissions of the four provinces (regions) were ranked as follows: Shaanxi > Ningxia > Gansu > Qinghai, maintaining a spatial pattern of higher emissions in the east and lower emissions in the west. c) Carbon emissions in prefecture-level cities (prefectures) in Northwest China showed a significant positive spatial correlation, mainly exhibiting high-high and low-low clustering. d) Technological progress and industrial upgrading had a suppressive effect on carbon emissions in Northwest China, but the suppressive effect was not significant. e) Urbanization, fossil energy consumption, and economic development were the main factors contributing to the growth of carbon emissions in Northwest China. This study recommends strengthening research on carbon reduction technologies, promoting “substantial” industrial structure upgrading, optimizing energy structure, and optimizing urbanization development models.

In order to reveal the spatio-temporal evolution of ecological resilience and its main influencing factors in the Yellow River Basin, and provide theoretical bases for the sustainable development of ecosystem and ecological environment governance in the Yellow River Basin, this paper took 2013-2023 as the research period, constructed the evaluation index system of ecosystem resilience, and used the entropy weight-TOPSIS method to measure the ecological resilience level of nine provinces (regions) in the Yellow River Basin. The Global Moran’s index was used to analyze the spatial autocorrelation of ecological resilience, the Dagum Gini coefficient was used to reveal regional differences in ecological resilience, and the random forest model was used to identify the main influencing factors of ecological resilience. The results show that: a) At the beginning of the study period, the ecological resilience levels of the nine provinces (regions) in the Yellow River Basin varied significantly, with particularly large disparities between upstream and downstream provinces (regions). During the study period, most provinces (regions) showed an upward trend in ecological resilience levels. Among them, Sichuan, Gansu, Henan, and Shandong exhibited a significant upward trend, while Qinghai, Ningxia, Inner Mongolia, Shaanxi, and Shanxi showed no obvious upward trend or experienced considerable fluctuations. Although inter-provincial disparities in ecological resilience levels narrowed by the end of the study period, the overall resilience remained generally low. b) The level of ecological resilience in the Yellow River Basin had a certain spatial autocorrelation, but the spatial autocorrelation was significantly weakened in the study period. c) Forest coverage rate, the level of industrial structure advancement, the water consumption rate of the ecological environment, the rationalization level of the industrial structure, and the proportion of infrastructure investment in fiscal expenditure were the main factors affecting the ecological resilience of the Yellow River Basin at present. SO₂ emissions per unit area, COD emissions per unit area, and the intensity of soil and water conservation investment remained non-negligible due to their historical significance. This study recommends increasing financial support to economically underdeveloped areas and ecologically fragile areas, vigorously promoting the green and low-carbon transformation of the economy, strengthening the unified allocation of water resources, and improving the efficiency of water resources utilization.

Scientifically quantifying the comprehensive level of ecological conservation and high-quality development in the Yellow River Basin and identifying its key influencing factors can provide a scientific basis for policy optimization and regulation. Based on data from nine provinces (autonomous regions) in the Yellow River Basin from 2011 to 2023, this study used the entropy weight method to measure the ecological conservation and high-quality development index (comprehensive index) for each province. The Dagum Gini coefficient was employed to analyze regional disparities, and the obstacle degree model was applied to identify the main influencing factors. The results show that: The overall comprehensive index of the Yellow River Basin exhibits an increasing trend, yet remains at a moderately low level. There is significant spatial heterogeneity in the comprehensive indices of the upper, middle, and lower reaches, generally following the pattern of lower reaches > middle reaches > upper reaches. The comprehensive indices of the nine provinces (regions) show pronounced spatial differentiation, with Shandong, Henan, and Sichuan exhibiting relatively high indices with stable growth rates, while Ningxia has the lowest index and the slowest growth rate. The overall Dagum Gini coefficient of the comprehensive index in the Yellow River Basin shows an upward trend, indicating continuously widening overall disparities, which mainly stem from inter-regional differences. The comprehensive index for the Yellow River Basin is primarily determined by a combination of key factors, including the completeness of flood control engineering systems, the level of　innovation capability, the intensity of water resource exploitation relative to ecological redlines, and the degree of flood risk.

To explore the coupling relationship between new quality productive forces in agriculture and ecological protection during high-quality agricultural development in the Yellow River Basin, this study utilized panel data (2014-2023) from eight prefecture-level cities in the Henan section. It constructed evaluation index systems for both agricultural new quality productive forces and ecological protection. Methods including the entropy weight method, the coupling coordination degree model, the obstacle degree model, and grey relational analysis were employed to systematically examine the coupling evolution characteristics, obstacle factors, and driving mechanisms. The results indicate that: The coupling coordination level between agricultural new quality productive forces and ecological protection in the Henan section of the Yellow River Basin improved steadily overall, with the average coordination degree rising to 0.930 by 2023, showing a transition from disorder to coordination. Sanmenxia and Zhengzhou exhibited higher coordination, while Jiaozuo and Puyang lagged relatively, revealing significant regional disparities. Structural misalignment was observed, with agricultural development outpacing ecological protection in some cities. Common driving factors included rural renewable energy application and high-standard farmland construction, whereas lagging regions relied more on water resource regulation and energy structure optimization. Accordingly, policy recommendations focus on regional synergy, technological penetration, resource regulation, and endogenous drive to facilitate the synergistic advancement of green agricultural transformation and high-quality development in the Yellow River Basin.

Prandtl’s classical mixing-length theory and the logarithmic velocity-distribution law derived from it have long formed an important foundation for turbulence research. However, the assumption of a mixing length proportional to the distance from the boundary is not fully consistent with observed flow fields. In addition, the resulting logarithmic law has two major theoretical deficiencies: a mathematical singularity at the wall and a nonzero velocity gradient at the location of maximum velocity. Most existing modifications are based on local corrections or empirical fitting and have not resolved these problems simultaneously. Some of them also fail to provide an explicit analytical solution or a clear physical interpretation.Through theoretical analysis and validation against measured data, this study reviews the development and physical basis of the turbulent eddy model, examines how it improves Prandtl’s mixing-length theory, and evaluates the contributions of the model and its associated velocity-distribution formula to hydraulics in three areas: fundamental turbulence theory, flow-resistance calculation, and bend hydraulics.The results show that the turbulent eddy model is developed from the physical process of turbulent eddy motion and establishes a relationship between the rotational kinetic energy and gravitational potential energy of turbulent eddies. This relationship leads to a physically meaningful vertical distribution of the mixing length. The resulting velocity-distribution formula eliminates the wall singularity and satisfies the zero-gradient condition at the location of maximum velocity while retaining an explicit analytical form. To the authors’ knowledge, the formula can accurately describe time-averaged velocity distributions and flow-resistance characteristics in clear-water and sediment-laden flows over hydraulically smooth and rough boundaries.Further developments based on the turbulent eddy model have produced analytical relationships for the vertical distribution and streamwise decay of bend secondary flow, its decay length, the near-bed flow direction, and the transverse water-surface slope. These results provide a new physically based and analytically tractable framework for turbulence research and its applications in hydraulics.

The Tangnaihai and Lanzhou stations are two major control hydrological stations in the Yellow River Basin. Quantitative analysis of the dependence and evolution of monthly runoff between these two stations provides critical support for the operation of water storage and compensation projects and the joint scheduling of water resources in the basin. Taking the implementation of the Yellow River Flood Control Operation Scheme in 2015 as a temporal breakpoint, monthly runoff data from 2005 to 2024 are divided into two periods: Ta  (2005-2014) and Tb (2015-2024). Copula functions are constructed for each period to quantitatively calculate probabilities under wet and dry conditions. The results indicate that: The conditional probabilities of wet and dry states in both periods are consistently significantly higher than the corresponding joint probabilities, revealing that the Tangnaihai Station exerts a distinct driving effect on runoff variations at the Lanzhou Station.  Compared with the Ta period, the joint probabilities of wet and dry states in the Tb period increase by 5.84% and 7.27%, respectively, while the conditional probabilities increase by 17.46% and 15.73%. This suggests that the synchronization of extreme states and the runoff dependence between the two stations have strengthened following the implementation of the Scheme. The findings elucidate the wet-dry dependence of monthly runoff between the two stations and quantitatively assess the reshaping effect of artificial interventions on hydrological synchronization.

To reveal the complex synergistic variation patterns of runoff and sediment in the Yellow River, a joint distribution model for runoff and sediment was constructed using two- and three-dimensional Copula functions based on runoff and sediment load data from three hydrological stations located in the upper-middle-lower reaches of the Yellow River Basin from 2002 to 2022. The encounter probabilities of abundant and deficient conditions for runoff and sediment transport load in the basin were calculated. The results indicate that: The runoff and sediment load at each hydrological station show a significant correlation at the significance level of P<0.01, with the strongest correlation observed at the Lijin hydrological station in the lower reach (Pearson and Kendall rank correlation coefficients were 0.958 and 0.823, respectively). The Gumbel and Gaussian Copula functions are found to be the most suitable for describing the two-dimensional joint distribution of runoff and sediment transport load within each hydrological station and the three-dimensional joint distribution of runoff or sediment transport load across different hydrological stations, respectively. At the hydrological station scale, the synchronous probabilities of runoff and sediment transport load are relatively high, with the maximum synchronous probability (77.35%) recorded at the Lijin hydrological station in the lower reach, following the order of simultaneous abundance > simultaneous normal > simultaneous deficiency. Among asynchronous encounters, the combination of “one normal and one deficient” exhibits the highest probability. At the basin spatial scale, the asynchronous probabilities of abundant or deficient conditions for runoff or sediment transport load across different hydrological stations are significantly higher than the synchronous probabilities (asynchronous probabilities: 70.80% for runoff, 66.54% for sediment transport load). Among synchronous encounters, simultaneous abundance has the highest probability. In the Yellow River Basin, the encounter of abundant and deficient conditions for runoff and sediment transport load is primarily synchronous within individual hydrological stations but predominantly asynchronous across spatial scales. The strongest synchrony occurs in the lower reach, while the most significant asynchrony is observed in the middle reach.

To improve the targeting and timeliness of flash flood warnings, loss assessment, and emergency decision-making, this study conducts a hazard assessment of flash flood disasters by integrating hydrological and hydrodynamic modeling. Based on this assessment, a characteristic database of high-hazard areas is constructed. Using machine learning and adopted rainfall characteristics as the dynamic evaluation indicator, a quantitative identification model for high-hazard areas of flash floods is established. The model is applied and analyzed in a typical watershed of the Longyangxia Reservoir area in the upper Yellow River. The results show that: The model can effectively identify high-hazard areas of flash floods, with recognition rates ranging from 71.4% to 100.0% under different verification scenarios and an average recognition rate of approximately 85%. This study provides a scientific basis and technical support for the accurate early warning of mountain torrent disasters, rapid loss assessment, and prompt emergency response and disaster relief.

Current research employing two-dimensional shallow water models to simulate dam-break flood routing lacks a systematic investigation into the causes of computational deviations arising from variations in grid size. To address this gap, this study summarizes the primary mechanisms by which grid size affects model outcomes, identifies specific modeling scenarios necessitating careful grid size consideration, and underscores the critical importance of grid resolution in dam-break flood simulations. By establishing a series of numerical models for plain reservoir dam-break floods across varying flood magnitudes and grid resolutions, this paper identifies two principal sources of deviation induced by grid size adjustments and proposes corresponding optimization strategies for grid sizing in dam-break flood modeling.

To analyze the utilization trends of water and soil resources in cultivated land within the Luohe River Basin of Henan Province, this study employed remote sensing and geographic information system technologies, based on land use data, meteorological data, and fundamental geospatial data spanning from 2000 to 2020. It utilized the Penman-Monteith formula, the Fu Baopu formula, and an empirical formula for effective precipitation to construct a water balance trend assessment model, thereby elucidating the patterns of cultivated land use change and its water balance impacts in the basin since 2000 at a grid scale. The results show that: a) Over the study period, the area of cultivated land in the Luohe River Basin of Henan Province exhibited a gradual decline.Dry farmland was primarily converted into grassland and construction land, while paddy fields were mainly distributed in patchy patterns along the banks of the Luohe River. b) The spatiotemporal disparities between actual evapotranspiration and effective precipitation resulted in pronounced regional variations in water supply and demand dynamics. Evapotranspiration capacity was robust in the southern basin and western regions of Lingbao City, diminishing progressively from the central to the eastern parts, whereas effective precipitation decreased from south to north. c) The water deficit trend markedly intensified across the entire study area, with the proportion of deficit regions escalating from 1.41% in 2000 to 12.46% in 2020. Notably, Luoyang City and its surroundings exhibited a heightened risk of water deficit. d) The water balance conditions of cultivated land changed substantially. In 2000, cultivated land predominantly experienced moderate drought and severe drought (accounting for 35.29% and 31.62% of the total cultivated land area), with severe water shortage areas comprising 19.23%. By 2020, the proportion of severe drought cultivated land had area risen to 42.17%, primarily concentrated in Xin’an County and Mengjin District within the basin. The irrigation water situation for cultivated land in the Luohe River Basin of Henan Province is increasingly unfavorable. Consequently, it is imperative to actively implement the “land allocation based on water availability” management strategy for the development and utilization of cultivated land.

In order to explore the synergistic relationship between grain security resilience and water resources carrying capacity in the Upper Yellow River, and to ensure regional grain security and sustainable water resources utilization, this paper took the five provinces (regions) in the Upper Yellow River as the research objects, constructed an evaluation index system for grain security resilience and water resources carrying capacity, and comprehensively employed the entropy method, the coupling coordination degree model, kernel density estimation, and the geographical detector to explore the spatiotemporal coupling characteristics and driving factors of grain security resilience and water resources carrying capacity from 2014 to 2023. The results show that: From 2014 to 2023, the comprehensive levels of both grain security resilience and water resources carrying capacity in the Upper Yellow River showed an upward trend, and the development gap between them gradually narrowed. The coupling coordination level improved from barely coordinated to primary coordination, and the inter-provincial differences decreased. Spatially, an uneven development pattern characterized by “high in the north and south, low in the middle” and “high in the south, low in the north” was observed. Gansu, Qinghai, and Ningxia remained at a low development level over the long term. Forest coverage rate, the number of employees in the rural primary industry, and the per capita water consumption were the main driving factors. It is recommended that the Upper Yellow River region make efforts in ecological protection, technological innovation, and policy support to promote the synergistic development of grain security resilience and water resources carrying capacity.

To identify the water resources carrying capacity (WRCC) and its influencing factors in the Tarim River Basin and reveal its spatiotemporal evolution, this paper built an evaluation index system including 21 indicators of four subsystems of water resources, society, economy and ecology. The game theory-based combination weighting method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model were employed to evaluate the WRCC of the five prefectures (regions) in the Tarim River Basin from 2013 to 2019. Furthermore, the obstacle degree model was applied to identify the major limiting factors affecting WRCC. The results indicate that: a) The overall WRCC of the Tarim River Basin exhibited a steady upward trend, improving from a relatively low level during 2013-2015 to a moderate level during 2016-2019. b) Significant spatial heterogeneity was observed in WRCC, with Bayingolin Mongolian autonomous prefecture exhibiting the highest carrying capacity, followed by Aksu prefecture, whereas Kizilsu Kirghiz autonomous prefecture, Kashgar prefecture, and Hotan prefecture showed relatively lower levels. c) Annual precipitation, water yield modulus, the proportion of ecological water use, water supply modulus, and gross domestic product (GDP) per capita were identified as the key factors influencing WRCC in the Tarim River Basin.

Water scarcity constitutes a major bottleneck to socio-economic development in Shandong Province. Assessing water stress is therefore crucial for understanding the regional water resource status. Based on data from the Shandong Provincial Survey and Statistical Bulletin, this study assessed the water stress in Shandong Province. It comprehensively employed Kernel Density Estimation (KDE), spatial autocorrelation analysis, and the geographical detector method to investigate the spatiotemporal evolution characteristics and key driving factors of water stress. The results indicate that: Shandong Province experienced a high overall water stress level, with a multi-year average index of 0.652 (2011-2022) , and exhibited significant spatial heterogeneity. Water resource pressure was relatively low in eastern Shandong, followed by central-southern Shandong, while northwestern Shandong faced relatively high water resource pressure. In terms of temporal evolution, water resource pressure in Shandong Province showed a trend of first rising and then fluctuating downward, and had gradually eased in recent years. Globally, water resource pressure in Shandong Province exhibits positive spatial autocorrelation with a high degree of aggregation. The proportion of added value of the primary industry and annual precipitation are identified as the main driving factors of water resource pressure changes in Shandong Province. Shandong Province should continue to strengthen water resource protection, improve the construction of water conservancy projects, enhance the capability of overall coordination and allocation of water resources, optimize the industrial structure of the regional economy, and improve water use efficiency, so as to realize the sustainable utilization of water resources and the harmonious development of society.

Alpine meadow soils store substantial amounts of organic carbon. Scientifically evaluating the impacts of land use change on carbon stocks is of great significance for optimizing territorial spatial planning. Taking Maqu County as a case study, this research utilized land use data from 2000 to 2023. The PLUS-InVEST model was employed to analyze the dynamic changes in land use types and carbon stocks. Future carbon stock dynamics under three scenarios in 2040 were projected. Furthermore, the optimal-parameter geographical detector method was applied to identify the primary driving factors of carbon stock changes. The results show that: Grassland and forest were the dominant land use types during the study period. Areas of forest, grassland, and unused land increased, while cropland and water bodies decreased. Carbon storage in Maqu County exhibited a fluctuating upward trend, with a net increase of 2.516×105 t, and showed a spatial pattern of “high in the northwest, low in the southeast”. Grassland was the main carbon source. By 2040, compared to 2020 levels, carbon storage is projected to decline by 4.948×105 t (natural development), 4.938×105 t (cropland protection), and 2.968×105 t (ecological protection). Land use and slope were the dominant drivers of the spatial differentiation of carbon storage in Maqu County. All pairwise interactions between driving factors exhibited bivariate enhancement. 

As emerging contaminants frequently detected in surface water, antibiotics may pose potential threats to the ecosystem of the Yellow River Delta. To safeguard the stability of this ecosystem, this study investigated the occurrence of antibiotics in the Yellow River Delta by region (current river course, abandoned channel, and concentrated aquaculture zone) and by season (April, June, August, and October 2023). The results indicate that:  All seven categories comprising 50 antibiotic compounds were detected in the surface water of the Yellow River Delta. Except for a slight increase during the water diversion and sediment regulation period, the cumulative concentrations generally followed the pattern of higher levels in the dry season than in the wet season.  Sulfonamides (SAs) were the predominant pollutants in the current river course. The abandoned channel was jointly affected by macrolides (MLs), quinolones (QNs), and SAs. In contrast, QNs and tetracyclines (TCs) constituted the primary antibiotic pollutants in the concentrated aquaculture zone.  Sulfamethoxazole (SMX), flumequine (FLU), ofloxacin (OFL), erythromycin (ETM), oxytetracycline (OTC), and lincomycin (LIM) were identified as the representative antibiotics in the surface water. Notably, SMX exhibited significant occurrence and posed a high ecological risk, qualifying it as a priority pollutant for regulatory control in this region.

Clarifying the spatiotemporal change characteristics and influencing factors of carbon (C) emission from land use is a vital basis for rational land planning and C emission reduction policies. Based on five periods of land use remote sensing data and energy consumption data, standard deviation ellipse analysis and geographic regression models were used to explore the spatiotemporal characteristics of C emission and their influencing factors in the context of land use in the Yellow River region of Henan Province from 2013 to 2021. The results show that: The amount of C absorption presented an increasing trend, while the net C emission amounts exhibited a “first rapid, then slowing” pattern in the Yellow River region from 2013 to 2021. The net C emission in the central region was significantly higher than that in the western and eastern regions. Standard deviation ellipse analysis indicates that the C emission center in the Yellow River region gradually shifted towards northeast from 2013 to 2021, suggesting that the northern and eastern regions had an increasing influence on the spatial pattern of C emission. The analyses show that population density, per capita social retail sales, and land urbanization were the main factors affecting C emission in the Yellow River region of Henan Province. In the future, the central and eastern regions with growing populations should make full use of the scale effect of population agglomeration and optimize and adjust the land use for C sink and C source. In addition, the land urbanization degree should be controlled, the increase in new C source lands should be restricted, and the level of intensive land use should be improved. In contrast, to achieve high-quality economic and social development, the western region should optimize the land use structure and layout while enhancing C sink capacity.

To provide a theoretical basis for the layout of Soil and Water Conservation (SWC) ecological construction and the achievement of phased SWC rate targets in Gansu Province, this study calculated the provincial and prefectural SWC rates for 2011, 2020, 2021, and 2022. These calculations were based on soil erosion data from the First National Census for Water Resources, dynamic monitoring results, and official Gansu Provincial SWC Bulletins. The historical trends of the SWC rate were analyzed. The effectiveness of SWC ecological construction is quantified using the reduction ratio of soil erosion area—defined as the proportion of eroded area reduced within a specific period relative to the total area of ecological construction implemented. By comparing SWC rate dynamics across different phases, this study examined the variations in eroded area reduction, ecological construction area, and their relationship with the SWC rate. The results indicated that: a) The provincial SWC rate exhibited a general upward trend from 2011 to 2022, with an average annual increase of 0.20 percentage points between 2020 and 2022. Significant regional disparities existed in the magnitude of increase; Prefectures in the central (Longzhong) and eastern (Longdong) Gansu regions showed relatively larger gains, whereas those in the Hexi Corridor region showed smaller increases. b) To achieve the 2025 phased target, the provincial SWC rate must increase by an average of 0.37 percentage points annually from 2022 to 2025. With the exception of Linxia Prefecture, where current erosion reduction rates (2020-2022) were sufficient to meet this target, all other prefectures were projected to fall short. Consequently, intensifying SWC efforts and expanding the area under governance were imperative. c) The reduction ratio of eroded areas remained low across the province. In 2021 and 2022, the provincial ratios were merely 10.86% and 14.99%, respectively. Even in Lanzhou, Qingyang, and Baiyin—which recorded the highest ratios in 2022 at 33.30%, 23.73%, and 22.22%, respectively—the figures remain modest. Therefore, it is recommended that prefectures adopt targeted governance strategies and tailored technical configurations based on local erosion typologies, socio-economic demands, and specific phased SWC targets to ensure the successful attainment of conservation goals.

Dike breaches pose a grave threat to public safety and property. As the core of emergency response, the intelligent generation of closure schemes and decision-making command rely heavily on a robust data backplane. The crux lies in efficiently aggregating and deeply integrating multi-source, multimodal data while ensuring secure storage and efficient retrieval. To achieve comprehensive information representation of hydraulic objects during dike breach closure, this study proposes a rapid construction method for such a data backplane. For diverse data sources, access methods including network connections, data buses, and file and database synchronization are adopted to enable rapid multi-source data convergence. For varied data modalities, an integrated storage scheme combining relational databases, non-relational databases, and object storage is designed to guarantee the efficient storage and retrieval of structured, semi-structured, and unstructured data. A case study of the dike breach closure at Tuanzhouyuan, Hunan Province, in July 2024, is presented. Based on the constructed data backplane, the initiation and closure processes of the breach are retrospectively simulated. The evolutionary trajectory of the breach is mapped and subsequently compared with real-time monitoring records. Results indicate that the simulated variation in breach width aligns closely with actual observations, validating the effectiveness of the proposed method. 

To refine, informatize, and modernize reservoir operation and management, and to provide practical references for the development of a digital twin water conservancy system, this study takes Guxian Reservoir as a case study to explore the key technologies and applications of a digital twin platform. A data backplane driven by multi-source data fusion was established leveraging integrated sky-air-ground-water-engineering sensing technologies. A multiscale coupled model was constructed, encompassing storage inundation, disaster assessment, and visual simulation. This model integrates a one-dimensional-two-dimensional coupled hydrodynamic mechanism model featuring time-varying parameters with a self-developed digital twin engine termed “Zhihe Shijie”. The digital twin platform of Guxian Reservoir plays a pivotal role in flood control dispatch, supporting the “Four Pre” capabilities (forecast, warning, prelude, and plan). It realizes dynamic simulation and visual display of flood routing, operational dispatch, and disaster assessment, thereby significantly enhancing decision-making capacity. Furthermore, this initiative provides a pioneering practical paradigm for the construction of a Digital Twin Yellow River. The development experience offers valuable insights for other water conservancy projects, while its core technologies and multi-scenario application modules facilitate the interconnectivity, co-construction, and sharing within the “2+N” business system of the Digital Twin Yellow River.

To address the issue of irrigation water scarcity in arid regions of Northwest China and achieve multi-dimensional intelligent water conservation, this study proposes a cotton water requirement prediction model based on meteorological factors. The model utilizes multi-year meteorological data and daily cotton water requirements, and combines the Genetic Algorithm (GA) and the Mind Evolutionary Algorithm (MEA) to optimize the Radial Basis Function (RBF) neural network, thereby constructing a cotton water requirement prediction model suitable for the straw drip irrigation planting pattern in Xinjiang. The results show that: Under identical meteorological input conditions, the GA-RBF model outperforms the standard RBF model, while the MEA-RBF model achieves higher prediction accuracy than the GA-RBF model and exhibits the fastest computational speed. Furthermore, inputting stage-specific meteorological factors during distinct cotton growth stages yields higher model accuracy compared to using uniform meteorological inputs across the entire growth period. The resulting MEA-RBF model demonstrates strong performance, with a RMSE of 0.386 1, a MAE of 0.272 8, and a NS value of 0.904 9.

Against the backdrop of constructing a limestone aggregate quarry, this study comprehensively applies hydrogeological investigation, pumping tests, geophysical exploration, and three-dimensional numerical simulation to systematically evaluate the exploitation potential of an expanded water supply site. It further explores the feasibility and effectiveness of achieving equivalent water source replacement through this expansion. The results indicate that:  The aquifer thickness in the study area ranges from 324 to 380 m, classifying it as a moderately productive aquifer with favorable conditions for water storage and regulation.  The total groundwater recharge is estimated at 4.660 7 million m³/a, with an allowable exploitable yield of 2.796 4 million m³/a.  Numerical simulations reveal that under the recommended extraction rate of 7 000 m³/d, the groundwater flow field will stabilize after 10 years. The maximum drawdown is approximately 72.20 m, with an influence radius of about 1.3 km, indicating controllable impacts on the ecology and surrounding domestic wells. Accordingly, it is recommended that this water supply site operate synergistically with other existing sites to collectively achieve the daily water supply target of 15 000 m³/d.

The synergy between water conservancy project resettlement and ecological protection is a key issue for high-quality development in the Yellow River Basin. Integrating the sustainable livelihoods framework, social-ecological system resilience theory, and global ecological threshold theory, this paper constructs a four-dimensional analytical framework of capital restructuring-synergy mechanism-resilience enhancement-ecological threshold and proposes three core concepts: capital conversion elasticity, synergy resilience, and ecological threshold adaptability. Taking the Xixiayuan Water Conservancy Project as a case study, the paper employs instrumental variable methods, regression discontinuity design, and other approaches to examine the interaction between resettlement institutional practice and ecological protection. The results show that: Migrants livelihood capital undergoes significant structural restructuring, and human capital and social capital exhibit positive causal effects on ecological participation. Resettlement and ecological protection achieve synergy through spatial planning, functional land rehabilitation, and industrial guidance, with a synergy degree index of 0.95. The biodiversity boundary adaptability is 0.830, approaching the threshold. It is necessary to strengthen ecological compensation and guard against cumulative risks. The paper proposes constructing a four-in-one institutional system of spatial planning-interest linkage-ecological compensation-threshold control.