In response to the issue that natural disaster knowledge graphs for single disaster types had a narrow coverage of information, making it difficult to extract knowledge from massive and complex information, this study proposed a method for building a natural disaster knowledge graph for the Yellow River Basin oriented toward loss assessment. The natural disaster knowledge graph consisted of a data resources layer, a knowledge extraction layer (including a schema layer and a data layer), and an application service layer. The schema layer was built by using a top-down approach, centered on ontological models of natural disaster events, fundamental geographic information, and disaster loss assessment. Multi-source heterogeneous data were collected, including natural disaster event data, basic geographic information data, and disaster loss data, and the data layer was built by using a bottom-up approach, enabling knowledge extraction, knowledge fusion, and knowledge storage from these diverse data sources. The application situations show that the knowledge graph supports efficient spatial-temporal relationship queries and rapid identification of regional concurrent disasters. The analysis of 160 major disaster events in the Yellow River Basin from 1981 to 2018 reveals an increasing frequency of disasters over time, with floods being the most common disaster type. Additionally, 37 instances of concurrent disasters are identified. This map breaks through the limitations of the traditional single disaster knowledge system and improves the efficiency of disaster loss assessment.

China is a country with severe earthquake disasters, with a wide range of affected areas, high frequency of occurrence, and high intensity of earthquake activity. Roads, as the "lifeline", play an important role in the transportation of materials and personnel. After an earthquake disaster occurs, quickly and accurately obtaining the location of road damage is of great significance for timely dredging of lifelines and carrying out post disaster rescue. In response to the issues of strong shadow interference, high fault missed detection rate, and severe fragmentation in remote sensing identification of road damage after earthquakes, this paper proposed a road damage layer extraction framework that integrated prior knowledge of OpenStreetMap (OSM). The effectiveness of the method was verified by using the 2023 Jishishan M6.2 earthquake as a typical case. By building a four layer technical system of "vector constraint-image segmentation-topology repair-damage detection", rapid localization of road damage in complex terrain areas had been achieved, providing assistance in improving rescue speed and reducing personnel and property losses.

Based on the random forest model and utilizing the sediment and water process data as well as climatic measurement data from four typical hydrological stations in the Zuli River Basin from 2001 to 2020, this study conducted the simulation and attribution analysis of the dynamic characteristics of sediment and water processes at the basin scale. The results show that the random forest model has good applicability for sediment and water simulation in the Zuli River Basin, with high simulation accuracy and a Nash-Sutcliffe Efficiency (NSE) greater than 0.5 for the vast majority of stations, but the simulation of data peaks is relatively poor. During the period from 2001 to 2020, the climate in the Zuli River Basin generally exhibited a trend towards warming and increased humidity, with an overall increasing trend in runoff and a decreasing trend in annual sediment transport. From 2010 to 2020, the changes in runoff in the Zuli River Basin are primarily influenced by climate change, with a contribution rate of 197.59%; whereas the changes in sediment are mainly reduced due to human activities, with a contribution rate of 162.46%.

There is independence and integration between water supply and sediment reduction in sediment-laden river reservoirs. How to maintain effective storage capacity and meet water supply requirements for a long time is one of the issues to be solved in the efficient operation of sediment-laden river reservoirs. In this paper, Dongzhuang Reservoir of Jinghe River was taken as the research object. Through the analysis of measured data and mathematical model calculation, the measured hydrological sediment and cross-section erosion and deposition in the lower reaches of Jinghe River and Weihe River were analyzed. The reservoir sediment discharge flow index which was beneficial to reduce the sediment deposition in the lower reaches of Weihe River and maintain the effective reservoir capacity for a long time was studied, and the joint regulation mode of reservoir runoff and sediment was put forward. The outcomes show that during the main flood season for the sediment interception period from July to September, when the inflow is greater than 600 m³/s and the sediment concentration is greater than 300 kg/m³, the Dongzhuang Reservoir is open for sediment discharge. As the normal operation period, during the main flood season from July to September, when the inflow exceeds 300 m³/s, the Dongzhuang Reservoir will open for sediment discharge. The reservoir cannot supply water during the sediment discharge period. The joint regulation of the Dongzhuang Reservoir and the surrounding four storage reservoirs can reduce the deposition of the lower reaches of the Weihe River by 11 million tons per year, increase the guarantee rate of agricultural irrigation from 30% to 50%, and increase the guarantee rate of industrial water supply from 57% to 95%.

In order to provide references for landslide hazard prevention and research on the sensitivity of landslide-causing factors, the Longyangxia-Jishixia section of the upper Yellow River basin was selected as the study area, and 16 factors such as elevation, slope, terrain roughness and lithology were taken as typical landslide hazard factors. The collinearity test was carried out by Spearman correlation coefficient method to select landslide hazard factors with strong correlation. GIS was used to reclassify landslide disaster-causing factors and analyze their weights with geographic detectors. The geographic detection model results were coupled with random forest model to obtain landslide prediction probabilities under different causative factors. ROC curve was used to verify the accuracy of prediction results. The results indicate that a）the explanatory power of the interaction between causative factors is greater than that of individual factors, with the synergistic effect of elevation and other topographic parameters being particularly significant. b）The importance of drainage density, topographic roughness, and profile curvature is nearly zero, suggesting that these features may not have a direct or significant correlation with landslide occurrence. c）There are notable differences in the contribution of causative factors to the prediction results, with the elevation-slope combination being the core driving unit for landslide development in the study area. d）The AUC value ofrandom forest model has achieved 0.93, indicating strong classification performance.

In order to scientifically evaluate the spatial-temporal characteristics of water-saving levels, identify key influencing factors, reveal the spatial equilibrium patterns in the Yellow River water-receiving area of Henan Province, provide a scientific basis for optimizing water resources allocation and formulate differentiated water-saving policies, a water-saving evaluation index system was built, encompassing five dimensions of comprehensive, agricultural, industrial, domestic, and ecological with 12 quantitative indicators. The TOPSIS method was employed to dynamically assess the water-saving levels of 14 prefecture-level cities in the Yellow River water-receiving areas of Henan Province from 2014 to 2023. Additionally, based on the DEMATEL method and spatial equilibrium analysis, the key influencing factors and their regional differentiation characteristics were systematically analyzed. The results indicate that a) from 2014 to 2023, the average water-saving level in the Yellow River water-receiving areas of Henan Province is classified as Level IV on a 5-level evaluation scale, indicating a relatively low level, with significant spatial heterogeneity in water-saving levels among prefecture-level cities. b) Using the DEMATEL method, five main influencing factors are identified and ranked by their degree of impact: the proportion of planned water users (C2) > water consumption per 10 000 yuan of GDP (C1) > effective utilization coefficient of farmland irrigation water (C5) > water consumption per 10 000 yuan of industrial added value (C7) > proportion of saved water (C3). c) The spatial equilibrium of water-saving in the study area generally remains relatively stable but exhibits a slight declining trend over time, reflecting potential risks of regional imbalance in water-saving development. Therefore, it is essential to strengthen water-saving policy guidance and optimize water resources allocation to ensure sustainable development.

With the advancement of water-saving technologies, China's industrial water use efficiency has been continuously improved, and the total industrial water use has shown a downward trend. The LMDI model was applied to analyze the driving factors of changes in industrial water use, and the rebound effect was used to quantitatively analyze the actual offset degree of the effectiveness of technological water-saving measures. An empirical analysis of the long-series panel data of Henan Province and its 18 prefecture-level cities from 2014 to 2022 shows that the improvement of industrial water use efficiency has effectively reduced the industrial water use, with the role of this factor being significantly enhanced. Meanwhile, economic scale and industrial structure have also contributed to a significant reduction in industrial water use, though there are large differences in their driving directions across different years and prefecture-level cities. On the whole, industrial water use in Henan Province is in a state of partial rebound effect. Driven by technological progress, the rebound effect value has decreased year by year, and the decoupling phenomenon between industrial water use and industrial added value has become obvious since 2019. Additionally, industrial water use in all 18 provincial-level cities also experience partial rebound, but there are significant regional differences (the rebound effect is relatively low in Xuchang, Pingdingshan and Kaifeng, while it is higher in Luohe, Anyang and Jiyuan). In order to alleviate the pressure of water resources shortage, reduce water environmental pollution and improve the level of industrial water conservation, controlling the rebound effect of industrial water use is essential. In order to achieve the high-quality development of Henan’s industrial economy, suggestions are put forward, including continuing to promote the improvement of industrial water use efficiency, coordinately advancing the formulation of industrial policies and water-saving policies, and building a regionally differentiated collaborative governance system.

In order to investigate the characteristics of microbial community and influencing factors in aquatic bodies during the rainy season in coastal cities, based on Illumina MiSeq sequencing, this paper studied the distribution characteristics of microbial community structure and its correlation with environmental factors in Xixiang River, Shenzhen, and analyzed the effects of environmental factors on microbial community structure. The results show that the nitrogen and phosphorus pollution of Xixiang River is serious, and the water quality of Xixiang River is poor Class V with the risk of eutrophication. There is no significant difference in microbial diversity among sampling sites. At the phylum level, Proteobacteria, Bacteroidetes and Actinobacteria are the dominant species, and Proteobacteria is the first dominant species with a relative abundance of 62.25%-77.28%. At the level of genera, the dominant genera at all sampling points are not completely consistent.  NH+4-N, TDS, NO-3-N, TN and TOC in river water are strongly correlated with the relative abundance of microorganisms, among which the microorganisms are  the most affected by NO-3-N, NH+4-N and TDS. The upstream is affected by the rehydration of reclaimed water from Gushu Sewage Plant, and the bacteria mainly removes organic matter, while the sewage and wastewater in the middle and downstream provide a good living environment for denitrifiers in the water body, resulting in lower nitrate concentration and increased NH+4-N concentration. In the rainy season, the Pearl River estuary is easily supported by the tidal tide of the Lingdingyang Sea area, which is suitable for the growth of Marivita.sp.

Understanding the trend of sediment load variation and future projections in the Ningxia-Inner Mongolia reach of the Yellow River is crucial for its management. This paper analyzed and summarized the characteristics of sediment load changes in the main stream and tributaries of this reach, and identified the causes for the sediment reduction. The characteristics of the sediment load variation in the Ningxia-Inner Mongolia reach (1960-2020) included: a decrease in sediment inflow, with a more pronounced reduction in the mainstem; altered sediment contribution ratio between mainstem and tributaries, showing increased proportional input from tributaries; distinct temporal inflection points in sediment changes for both mainstem and tributaries, with recent reduction phases being largely synchronous and; recent sediment load variations approximately follow a lognormal distribution. The main driving factors influencing these changes of sediment inflow included the detention of the main stream reservoir, water and soil conservation measures in the tributaries, and the variation of rainfall. Considering long-term rainfall stability with cyclical fluctuations and diminishing reservoir sediment retention capacity over time, this study based its analysis on actual sediment yield conditions during 2000-2020, by evaluating reduced sediment interception capacity and newly implemented conservation measures, it is projected that the annual sediment load at Xiaheyan Station on the mainstem, and annual sediment input from interval tributaries will both increase moderately compared to recent levels.

Through applying technologies such as digital twin, artificial intelligence, mobile communication, and the Internet to enable intelligent management of the Yellow River conservation and governance, the construction of digital twin Yellow River can realize the real-time monitoring, precise early warnings, efficient command and dispatch, and scientific decision-making. In order to provide reference for the digital twin Construction in the Yellow River Basin and nationwide, this paper analyzed the “Three Yellow Rivers” construction system of Yellow River Conservancy Commission (YRCC), particularly the progress and achievements in the construction of digital twin Yellow River. Focusing on the improvement of capabilities of flood control project safety and flood defense in the lower reaches of the Yellow River, this paper proposed the key priorities for digital twin flood control project construction: strengthening the integrated “sky-space-earth-water-project” monitoring and sensor network, establishing data aggregation, governance standards, and update mechanisms, improving the data foundation for flood control projects, accelerating the integration of mathematical models with flood control project data, enhancing the “Three Yellow Rivers” linkage and business applications.

Reservoirs are significant emission sources of methane (CH4), and methanotrophs can mitigate their emissions by oxidizing CH4. In order to comprehend the community characteristics, gene abundance, and assembly processes of methanotrophs in the reservoir sediments of the Huangshui River Basin on the Qinghai-Tibet Plateau, surface sediments from eight reservoirs were collected respectively in May 2023 (dry season) and August 2023 (wet season). Based on real-time fluorescence quantitative PCR and sequencing technology of the functional gene pmoA of methanotrophs, the abundance, community composition, and the diversity of methanotrophs were analyzed, and the assembly processes of methanotrophs were analyzed using the neutral community model. The results show that at the phylum level, the methanotrophs in the Huangshui River Basin are mainly composed of Proteobacteria. At the genus level, they are mainly constituted by Methylocystis and Methylobacter. The α diversity is manifested as being higher in the wet season than in the dry season, while the β diversity is not significant. The abundance of the pmoA gene in the dry season is significantly higher than that in the wet season. The assembly processes of methanotrophs in reservoir sediments are dominated by stochastic processes, among which drift is the most powerful. Temperature, total nitrogen, and pH are the main factors influencing the methanotroph community, and sediment pH is the dominant environmental factor for the abundance of the pmoA gene.

In order to reasonably predict the future water demand situation in Henan Province, considering population scale and economic size, this study built a water demand forecasting method based on social characteristics to project the changes in water demand from 2025 to 2035. The results indicate that a decreasing trend in the total water demand for Henan Province in the future, with the total water demands for 2025, 2030, and 2035 being 21.795 billion m³, 21.198 billion m³, and 20.369 billion m³, respectively, representing reductions of 8.11%, 10.63%, and 14.03% compared to 2020. The proportion of water demand across different sectors is ranked as agriculture>domestic>ecological>industrial, with the share of water demand in agriculture and industry showing a decreasing trend, while the share of water demand in domestic use and ecological needs is increasing. The future population change in Henan Province is relatively small, with urban population growth significantly impacting domestic water demand. There is a negative correlation between economic growth and changes in water demand in Henan Province. The increase in water resources utilization efficiency is a primary factor contributing to the reduction in agricultural and industrial water demand, and is also the reason behind the overall decreasing trend in water demand. The rising level of urbanization and improvements in economic and social living standards are important driving forces behind the changes in future water demand in Henan Province.

It is a common method to extract water areas in SAR remote sensing images based on the threshold segmentation method, which has the advantages of clear physical meaning and low algorithm complexity. The determination of threshold is the key of this type of method, and the existing manual and automatic threshold determination methods suffer from poor timeliness and weak adaptability to water distribution. This article firstly analyzed the reasons for the fluctuation of the optimal segmentation threshold when extracting water bodies based on SAR remote sensing images from the perspective of microwave scattering characteristics of water bodies, mainly including imaging conditions, polarization methods, water surface roughness, and other factors; Secondly, on this basis, a regression model between SAR imaging conditions and water backscattering coefficient was built , and an adaptive threshold segmentation method was proposed for water extraction based on this model. Finally, experiments were conducted by using actual high-resolution SAR remote sensing image data. The test results show that the method has strong adaptability to changes in imaging conditions and other factors, with an extraction accuracy of 94.8%. The extraction process can achieve full process automation, which can effectively improve the accuracy and timeliness of remote sensing flood monitoring.

Strong earthquakes will greatly reduce the stability of the reservoir slope and easily induce landslide geological disasters. The superposition of earthquake and landslide surge load greatly threatens the safety of the dam body. In order to explore the dynamic response and damage evolution of high arch dam under the superposition of earthquake-landslide surge, this paper took a high arch dam as the object, built  a fine finite element model, determined the calculation model of earthquake-landslide surge load, and analyzed the modal variation law, displacement response characteristics and damage evolution trend of arch dam under multiple working conditions. The results show that the hydrodynamic added mass significantly reduces the wet modal frequency of the arch dam by 18%-23%, and the high-order vibration modes change significantly. When the earthquake and surge are superimposed, the peak displacement Rd of the midpoint of the vault is positively correlated with the peak acceleration of the earthquake and the maximum surge height. When the peak acceleration of the earthquake increases from 0.2g to 0.6g, Rd increases by 89.7%. The maximum displacement time under different working conditions is affected by many factors. The damage degree of dam body varies greatly under different working conditions. The damage of upstream surface is sensitive to the change of surge height. When the surge height is different by 40 m, the weighted damage area ratio of upstream surface to RUWA changes by 27.1%. From condition one to condition three, the weighted damage area ratio of cantilever surface is increased from 9.99% to 25.76% compared with RFWA, and the dam body has penetrating cracks. The damage dissipation energy increases sharply with the increase of load strength.

In order to curb the severe wind erosion in the Great Bend Region of the Yellow River and reduce aeolian sediment input, this study investigated the aerodynamic mechanisms of sand transport and clarified the underlying principles and scientific issues of sand arrestation. Turbulent velocity distribution formulas incorporating basal roughness and concentration distribution models typical of desert environments were applied to analyze the wind speed, sediment concentration, and sand flux during dust events. The validation against field observations and theoretical calculations reveals a clear inverse relationship between sediment flux and surface roughness, indicating that sand-control engineering effectively weakens both wind erosion intensity and sand production under strong winds. Further calculations using threshold velocity formulas that account for drag effects show that the entrainment threshold of sand particles is positively related to surface roughness. Natural desert surfaces with low roughness exhibit lower threshold velocities, intensifying wind erosion, whereas the installation of sand barriers increases surface roughness, which simultaneously raises the entrainment threshold and reduces near-surface wind velocity. Under this dual effect-enhanced threshold and diminished near-ground wind speed-the activity of aeolian sand is significantly suppressed. This demonstrates that the principle of sand-control engineering lies in increasing surface resistance to restrain sand mobility. In contrast, smooth-surfaced control structures hinder particle deposition atop dunes, thereby suppressing dune migration and expansion. Based on the principle of minimum energy dissipation in natural systems, we have proposed aligning sand-control layouts along the most stable dune ridge lines. Meanwhile, the overall configuration of control structures, optimized under the principle of minimum resistance, not only modifies near-surface wind fields but also exhibits multi-directional adaptability through its crest morphology.

Due to its complex terrain and special climate, Qinghai Province is prone to sudden and destructive mountain floods. In order to provide a basis for the monitoring and prevention of mountain floods in the region, taking the Longyangxia-Jishixia section of the upper reaches of the Yellow River in Qinghai Province, where mountain flood disasters were relatively severe, as the study area, 10 influencing factors of mountain flood disasters were initially selected. Based on the data of 115 historical flood disaster points in the study area from 1958 to 2000, four factors with strong correlations were eliminated through Pearson correlation test. The remaining six influencing factors were classified. GIS spatial analysis technology was used to obtain the classified data of the six influencing factors. The entropy index method was adopted to calculate the weights of each factor and identify the main disaster-causing factors. The research results show that elevation, annual precipitation, terrain roughness, NDVI, distance from the river course, and aspect are the disaster-causing factors of mountain floods in the study area (with the weights of 0.571 6, 0.144 8, 0.107 9, 0.094 8, 0.071 9 and 0.009 0 respectively), among which, elevation, annual precipitation and terrain roughness are the main disaster-causing factors. According to the classification of the main disaster-causing factors, 91.30% of the historical mountain flood disasters in the study area occur in the areas with an elevation lower than 3 091 m, 99.14% occur in the areas with an annual precipitation greater than 317 mm, and 98.26% occur in the areas with a terrain roughness less than 1.10.

In order to explore the realistic path of new quality productivity to empower urban economic resilience in the Yellow River Basin, and provide a reference for the implementation of the major national strategy of ecological protection and high-quality development in the Yellow River Basin, based on the panel data of 99 sample cities in the nine provinces (autonomous regions) of the Yellow River Basin from 2011 to 2022, the entropy method was adopted to measure the level of new quality productivity and the urban economic resilience index. Moreover, the two-way fixed effect model and the mediating mechanism model were used to empirically analyze the impact of new quality productivity on the urban economic resilience of the Yellow River Basin and its mechanism of action. The results show that on the whole, the new quality productivity has a significant role in promoting the urban economic resilience of the Yellow River Basin, and its internal mechanism is to promote the upgrading of industrial structure and improve the level of infrastructure construction. The effect of new quality productivity is heterogeneous, especially in the middle reaches of the Yellow River Basin, small-scale and high-intensity environmental regulation cities are stronger. Some policy suggestions are proposed, such as actively cultivating and developing new quality productive forces, promoting the upgrading of industrial structure in the Yellow River Basin and implementing differentiated regional development strategies.

In order to explore the impact of green technology innovation in the cities of the Yellow River Basin on carbon emission intensity and its spatial spillover effects, and to provide references for promoting ecological protection and high-quality green low-carbon transformation in the Yellow River Basin, based on the panel data from 79 prefecture-level cities in the Yellow River Basin from 2005 to 2021, the study measured the level of green technology innovation and carbon emission intensity in these cities, applied a spatial Durbin model for regression analysis and robustness testing, and analyzed the impact of green technology innovation on carbon emission intensity along with its spatial spillover effects, regional heterogeneity, and resources endowment heterogeneity. The results indicate that a) the level of green technology innovation in the cities of the Yellow River Basin has steadily improved while carbon emission intensity has significantly decreased during the study period, with both showing significant spatial inequity. b) Urban green technology innovation can effectively reduce carbon emission intensity, and the indirect carbon reduction effect on neighboring cities is greater than the direct carbon reduction effect in the city itself. c) The carbon reduction effects of urban green technology innovation exhibit regional heterogeneity and resources endowment heterogeneity, with downstream cities showing significant spatial spillover effects from green technology innovation while upstream cities have not yet formed significant spatial spillover effects. Resources-based cities have a greater direct effect of green technology innovation, while non-resources-based cities have a larger indirect effect. d) The spatial spillover effect of urban green technology innovation on carbon emission intensity shows an N-shaped variation with increasing geographical distance, with the optimal geographical distance being 600 km. Recommendations: a) Continue to increase support for green technology innovation in the Yellow River Basin, enhancing the training and introduction of talents for green technology innovation to improve innovation capabilities. b) Build a collaborative green technology innovation system across multiple cities and improve the mechanisms for green technology diffusion, etc., to fully leverage the spatial spillover effects of green technology innovation from central cities, downstream cities, and non-resources-based cities, enabling green technology innovation to play a greater role in overall carbon reduction and emission reduction in the basin.

The integrated control of small watersheds in the Yellow River Basin is an important part of implementing the national strategy of ecological protection and high-quality development in the Yellow River Basin. In view of the control issues caused by the stepped landform, the characteristics of the climate-vegetation transition zone and the vulnerability of the cascading ecology within the basin, the core contradictions of the comprehensive management of small watersheds were analyzed from three perspectives. In terms of the natural system dimension, it was reflected in the dual pressures of resources and the environment faced by the upstream, midstream and downstream respectively. In terms of the technical system dimension, it was reflected in the lag between the rigid constraints of the resources background and the adaptability of management technologies. In the dimension of the management system, it was reflected in the fragmentation of cross-departmental rights and responsibilities, weak cross-regional collaborative capabilities, and the imbalance between protection and development goals. Building upon this analysis, this study proposes pathways to address the systemic challenges in integrated small watershed management: establishing a resilience enhancement pathway centered on “soil and water conservation, resources efficiency improvement, ecological restoration and climate adaptation”; developing a dynamic intelligent zoning and digital twin decision support system; devising a cross-domain authority-responsibility integration mechanism and a trilateral compensation system for water quality, quantity and sediment; and creating an eco-industrial value-added chain with ecological credit conversion channels. These proposals provide scientific underpinnings for overcoming the systemic challenges in integrated small watershed management within the Yellow River Basin and exploring pathways to improve its quality and efficiency.

In order to scientifically evaluate the level of high-quality development in the Yellow River Basin and explore its spatial differentiation and influencing factors, and then provide a breakthrough point for policy selection to promote high-quality coordinated development in the Yellow River Basin. Based on the concept of strong sustainable development, using the panel data of 81 prefecture-level cities in the Yellow River Basin from 2011 to 2020, measuring the total factor productivity by the the super-efficiency mixed measurement model to represent the level of high-quality development. The Dagum Gini coefficient and Moran index were employed to examine the spatial-temporal differentiation characteristics, and the spatial Durbin model was utilized to explore the influencing factors and spatial spillover effects. The results show that a) the high-quality development level of the Yellow River Basin shows a fluctuating upward trend. The phased deterioration of efficiency change effects hinders high-quality development. Technological progress effect is the main driving force for high-quality development, but it has already shown signs of weakening. b)The spatial differences in the level of high-quality development in the Yellow River Basin are significant and are increasing. The spatial non-equilibrium of total factor productivity within and among the upstream, midstream and downstream regions has shown a synchronous strengthening trend, and the inter-regional differences are the primary cause of the spatial differences in high-quality development in the basin. c)There is a significant spatial correlation in the level of high-quality development among the prefecture-level cities in the Yellow River Basin. d)The influencing factors like environmental regulation, technological innovation, opening up and urbanization are the stable driving factors for high-quality development, and each of these driving factors has different spatial spillover effects.

In order to address climate change and water resources pressures, and to achieve sustainable regional water resources utilization under the carbon neutrality target, the InVEST model was employed to assess carbon storage and water yield in the Qinhe River Basin from 2000 to 2020. The study also used geographical detectors to explore the driving factors and explanatory power, and spatial autocorrelation analysis to examine the spatial relationship between the two. The results show that: a) Water yield in the Qinhe River Basin has shown a fluctuating increasing trend, rising from 1.020 billion m³ in 2000 to 1.167 billion m³ in 2020. This change aligns with the trend in precipitation, with carbon storage and potential evapotranspiration being the main driving factors. b) Carbon storage decreases from 167.566 7 million tons in 2000 to 167.110 5 million tons in 2020, following a trend similar to soil carbon storage, with potential evapotranspiration and water yield being the primary driving factors. c) The global Moran’s index of water yield and carbon storage is -0.2, showing no significant spatial distribution overall. Spatially, there is a pattern of high water yield-low carbon storage and low water yield-high carbon storage.

In order to effectively integrate raster-based remote sensing monitoring results of soil erosion with plot-based (land use patches) soil and water conservation management, and to enhance the application of dynamic soil erosion monitoring outcomes in conservation practices, this study proposed a method and standard for categorizing land use patches based on practical experience in remote sensing image interpretation. Using land use patches derived from dynamic soil erosion monitoring as the basic evaluation unit and raster-based monitoring results as the foundation, land use patches were classified into five types of non-urgent treatment, desirable treatment, preventive protection, industry management, and non-soil erosion. The categorization criteria were determined based on topographic slope, vegetation cover, proportion of soil erosion area, and whether the responsible entity for soil erosion prevention and control was clearly defined. In Yunyang County, where hydraulic erosion dominates, the application results align with local conditions and meet the requirements of soil and water conservation management.For regions with mixed wind and hydraulic erosion, areas dominated by other erosion types, or locations with special conservation management needs, the categorization methods and standards can be adjusted accordingly during land use patch classification.

Based on the development of method, theory and the legislation in the process of Yellow River management, this paper proposed the philosophical concept of “Method, Theory, Legislation and Daoism” in Yellow River management, analyzed the basic principles and rules of dialectical materialism reflected in it, and demonstrated its philosophical scientificity, rationality and the dialectical relationship between them. Through reviewing the ancient river management ideas, analyzing the People’s Yellow River management at different stages, and comprehending the profound essence of the new era’s water management ideas in Yellow River management, we aimed to explore the concepts of “Method, Theory, Legislation and Daoism” in it, exploring its dialectical development in the practice of Yellow River control in various historical periods. Analyzing that the Yellow River control is a comprehensive process of the method progress, the ideological development, and the legislation improvement, which is a historical practice of the coordinated development of “Method, Theory, Legislation and Daoism”. The protection and management of the Yellow River should innovate the method of river management, study the theory of water management, clarify the legislation of watershed harnessing and follow the Daoism of harmonious coexistence between humans and water.

In order to reveal the decoupling effects of carbon emissions in urban agglomerations within the Yellow River Basin (YRB) and identify their key influencing factors, this study aimed to provide a scientific basis for formulating effective carbon reduction policies, and advanced the national strategy of ecological protection and high-quality development in the YRB. In this study, the Tapio decoupling index model and LMDI model were comprehensively adopted to analyze the decoupling status of carbon emissions of urban agglomerations in the YRB and their temporal and spatial changes, identify the key factors affecting the carbon decoupling of urban agglomerations, and propose suggestions for the green and low-carbon development of urban agglomerations. The results show that: a) from 2001 to 2020, the carbon emissions of all urban agglomerations in the YRB are on the rise, and the carbon emissions from high to low are Shandong Peninsula urban agglomerations, Central Plains urban agglomerations, Guanzhong Plain urban agglomerations, Lan-Xi urban agglomerations, Jinzhong urban agglomerations, Hu-Bao-E-Yu urban agglomerations and Ningxia Yanhuang urban agglomerations. b) The type of carbon decoupling in urban agglomerations in the YRB is mainly weak, but the carbon decoupling index generally increases from time to time. Therefore, according to the existing economic development pattern, the economic development of urban agglomerations in the YRB is difficult to get rid of the dependence on fossil energy in the short term, and the road to carbon emission reduction is still a long way to go. c) Energy intensity, per capita GDP, technological level, and the population carrying capacity of the real economy are the main factors influencing the decoupling of carbon emissions in urban agglomerations within the YRB. Improving energy efficiency and technological capability, optimizing industrial structure, and enhancing the population carrying capacity of the real economy can effectively promote an ideal decoupling between economic growth and carbon emissions.

In order to empower the promotion of the new stage of high-quality development of water conservancy, and continue to promote the construction of the digital twin Yellow River, we constructed the digital twin-based Jiaozuo Qinhe “Four Predictions” integration platform, applied it to the Qinhe River Basin in Jiaozuo section, and explored the key technologies and application scenarios for the construction of digital twins of the Qinhe River in Jiaozuo section. The key technologies included the construction of hydraulic professional models and high-fidelity digital twin simulation engines, which utilized a high-performance aggregate hydrological model, a high-efficiency flood evolution model, and a visual disaster assessment model for flood forecasting, preview simulation and disaster assessment, and built an integrated data base for “air, space and ground” through multi-dimensional and multi-temporal and spatial scales. In addition, it formed an integrated platform for the “Four Predictions” of the Jiaozuo Qinhe River, which included dynamic monitoring, forecasting, early warning, rehearsal and preplanning, and described the platform’s infrastructure, functions and application achievements. After the platform is put into application, it will realize the dynamic interaction, real-time integration and simulation of the flood forecast and dispatching results of the Qinhe River in the digital map, can more accurately assess the flood situation, achieve timely early warning and rapid response, gain the greatest initiative for flood disaster prevention, effectively enhance the flood monitoring and early warning capabilities and scientific decision-making capabilities of the Jiaozuo Qinhe River Basin, and at the same time provide construction ideas and case references for the construction of the “Four Predictions” platform in other small and medium-sized river basins.

As a result of the heavy rainfall, flooding remains in the later stages of the rainfall and may continue to cause harm and impact. In order to accurately predict the depth and duration of urban flooding and waterlogging, the RF-LSTM model was proposed to address the difficulty of simulating floods in the later stages of the heavy rainfall. Based on the SWMM model-simulated flood data in Zhengzhou City, China, the flood depths at three representative flooded points were simulated by using the proposed model, and the flooding process caused by rainfall under different recurrence periods was predicted. The results show that compared to the single LSTM model, the simulation accuracy of the RF-LSTM model has been improved, verifying the applicability of the model in flood simulation. The growth rates of flood duration and the maximum flood depth at flooded points are the highest under the 1-2 a return period, therefore the existing drainage system should be renovated or redesigned.

Yulin in Northern Shaanxi is rich in high-quality coal resources. However, large-scale coal mining has caused severe damage to regional water resources. Taking Yulin coal mine as the study area, this study built a Relative Risk Model (RRM) to quantify the stress effects of risk sources including industrial development, mining-induced collapse and groundwater drainage on four types of receptors of social water stress, underlying surface, vegetation ecology and water resources. By dividing 84 watershed risk units, the study used log-normalization of risk values and natural break classification to zone the study area into five risk levels, proposing differentiated protection strategies. The results show that the mining-induced collapse is the primary risk source (contributing 52% of the risk value). The underlying surface and vegetation ecology are sensitive receptors (accounting for 35% and 28% of the risk value respectively). Level I risk areas require prioritized surface restoration and comprehensive utilization of drained water, while Level V areas need to be given attention, and buffer zones should be delineated.

In order to investigate the effect and mechanism of digital economic development on carbon emission in the Yellow River Basin, based on the panel data of 76 prefecture-level cities in the Yellow River Basin from 2011 to 2020, we measured the level of digital economic development, the total amount of carbon emission and the intensity of carbon emission in the Yellow River Basin, and built an individual and time two-way fixed-effects model to conduct empirical analysis, and conducted robustness tests on the results of the lagging effect of digital economic development, changing the sample capacity, and substitution variables. The empirical results are tested for robustness such as lagged effect of digital economic development, changing sample capacity, and substitution of variables, the mechanism of technological progress and industrial structure upgrading, and the heterogeneity of location and heterogeneity of resource endowment of carbon emission reduction effect of digital economic development. The results show that a) the digital economic development has a significant inhibitory effect on carbon emission intensity and total carbon emission in the Yellow River Basin. b) Technological progress and industrial structure upgrading are important mechanisms for digital economic development to promote carbon emission reduction in the Yellow River Basin. c) There is significant location heterogeneity and resources endowment heterogeneity in the inhibitory effect of digital economic development on carbon emission in the Yellow River Basin, and the inhibitory effect on carbon emission in the middle and upstream areas of the Yellow River is significantly better than that in the downstream areas, and the inhibitory effect on carbon emission in the middle and downstream areas is significantly worse. The inhibition effect on the total carbon emissions in the middle and upper reaches of the Yellow River is significantly better than that in the lower reaches, the inhibition effect on the carbon emission intensity in the upper reaches has not yet appeared, and the inhibition effect on the carbon emissions of non-resources cities is significantly greater than that of resources cities. Countermeasures and suggestions are put forward to coordinate the coordinated development of the digital economy in the Yellow River Basin, strengthen the promotion of green and low-carbon technological innovation, accelerate the transformation and upgrading of the industrial structure, implement differentiated digital economy development strategies, and effectively curb carbon emissions.

In order to effectively support scientific decision-making for ecological protection in the Yellow River Basin, with digitization, networking and intelligence as the main lines, and based on the characteristics of the ecological environment in the basin, a digital twin platform for ecological protection in the Yellow River Basin was constructed. A model framework including information infrastructure, data base, model and technology simulation, business applications was designed. By classifying and compiling monitoring data on water resources, water ecology and water environment, it established a comprehensive data system for the entire basin. Integrated data collection and monitoring, big data integration and analysis, cloud computing and edge computing integration, digital twin modeling and simulation and other technologies were used to realize the data aggregation and presentation of ecological environment factors such as ecological environment status, natural reserve distribution, ecological flow guarantee and so on. Through platform ecological data visualization, ecological simulation and ecological perspective application practice, the water function zoning and statistical situation of the Yellow River Basin, the evolution of key protected animals and plants in the estuarine delta, the evolution of land use types and the inundation range of the Jingtai Stone Forest caused by the Heishanxia Water Control Project were demonstrated, enhancing the multi-source data aggregation governance and scientific decision-making for ecological protection in the Yellow River Basin.

Currently, the frequency and intensity of extreme climate events have significantly increased, making the safety risks of reservoir overtopping and dam breaches more prominent. This study investigated the overtopping-induced breach process through a combination of generalized flume experiments and mathematical theoretical analysis. The results indicate that compared to coarser-grained dam materials, fine-grained dam bodies exhibit slower seepage rates and weaker permeability. As the upstream water level rises, the dam material gradually becomes saturated, with the saturation rate accelerating as the water level rises faster. The initiation of surface particle movement is identified as the key factor triggering erosion damage, while the upstream retreat of the scarp is critical to the occurrence of a breach. Based on the breach process, a geometric generalization model for the longitudinal and lateral development of the breach is proposed. Furthermore, by applying calculus principles, the flood discharge process during overtopping failure is analyzed, demonstrating that the flood release process can be regarded as the cumulative effect of various breach-influencing factors. Mathematical expressions for breach development and discharge variation at different stages are also derived. 

In order to explore the water-saving efficiency of floating balls on large water bodies in the arid regions of northwest China, this study was based on a water surface shading experiment conducted in Kunyu City of Hetian Prefecture. The experiment utilized two Φ20 standard evaporation pans, six 20 m² evaporation ponds, and one 3 000 m² evaporation pond as evaporation devices, with the covering material being HDPE black weighted floating balls with a diameter of 10 cm. The study mainly analyzed the differences in annual evaporation between the Φ20 standard evaporation pans and the 20 m² evaporation ponds and calculated the evaporation conversion coefficient between the two. Additionally, by analyzing the stability of the floating balls in the 3 000 m² evaporation pond under different wind speed conditions, the relationship between floating ball coverage area and water-saving rate was explored. The study primarily reveals that the main cause of the evaporation differences between the Φ20 standard evaporation pans and the 20 m² evaporation ponds lies in the variation in internal water temperature and the heat supply differences caused by the wall effects. The evaporation conversion coefficients are 0.587 during the non-freezing period and 0.282 during the freezing period. When the wind speed exceeds 4 m/s, the blank water area under the floating ball coverage shows a nonlinear positive correlation with wind speed, expressed by the equation y=0.070 68x1.913 69, the floating ball coverage rate and water-saving rate decrease as wind speed increases.

In order to provide a scientific theoretical foundation for promoting the coordinated development of new quality productivity between the Yellow River Basin and Yangtze River Basin, and provide decision-making references for formulating more rational regional development policies, this study established an evaluation index system for regional new quality productivity development. Employing methods such as entropy method, Theil index, spatial correlation analysis and QAP analysis, a comparative empirical investigation was conducted on the development levels and influencing factors of new quality productivity in both basins from 2013 to 2022. The results show that a) the development level of new quality productive forces in the Yangtze River Basin is generally higher than that in the Yellow River Basin. The spatial distribution of the development of new productive forces in the two major river basins has a distinct “block segmentation” feature. The development levels of both show a pattern of increasing successively from the upper to the middle and lower reaches. The multi-polarization phenomenon in the Yellow River Basin is more obvious than that in the Yangtze River Basin. b) The intra-regional and inter-regional differences in the Yangtze River Basin has decreased significantly, with a turning point occurring in 2019 when inter-regional differences fall below intra-regional differences for the first time, signaling a shift toward intra-regional variance dominance. Conversely, the differences between eastern and western regions within the Yellow River Basin, along with intra-regional differences in western areas, display an expanding trend. c) The global spatial autocorrelation of new quality productivity development in both basins shows continuous growth during 2013-2022, reflecting intensified spatial agglomeration. The provincial-level spatial correlation intensity in the Yellow River Basin remains weaker than that in the Yangtze River Basin. d) The regional differences in future-oriented industries and green development emerge as the strongest drivers of new quality productivity differences in the Yangtze River Basin, while innovation-driven industrial development levels and production materials differences constitute the predominant influencing factors in the Yellow River Basin. Based on these findings, the study has proposed the recommendations including optimizing resources allocation to enhance regional equilibrium, implementing innovation-driven strategies with differentiated approaches for cultivating new quality productivity, refining targeted policy frameworks, and strengthening inter-regional collaborative development mechanisms.

Exploring the spatial-temporal characteristics and influencing factors of the new and old growth drivers conversion in the Yellow River Basin is crucial for fostering high-quality development in the basin. The evaluation index system was built according to the dimensions of new and old growth drivers, and the Entropy Weight-TOPSIS method and the GMM model were introduced to portray the spatial-temporal characteristics and the influencing factors of the new and old growth drivers conversion in the basin. The findings reveal several key insights: a) The process of transforming old and new growth drivers in the Yellow River Basin can be divided into three distinct stages of “fluctuating rise-slow decline-steady rise”, ultimately leading to a steady upward trajectory. This trend reflects the alternation and replacement of the driving forces behind economic growth in the basin. b) Significant disparities exist in the level of new and old growth drivers  conversion among the upper, middle, and lower reaches of the Yellow River Basin, resulting in a spatial distribution pattern characterized by higher levels in the east and lower levels in the west. c) Regarding influencing factors, labor force, infrastructure, informationization, technology research and development, and high-end human resources exert positive effects on the conversion of old and new growth drivers in the basin. Conversely, financial development negatively impacts this conversion process, while the influence of capital remains non-significant. Therefore, it is imperative for the Yellow River Basin to prioritize the cultivation of new growth drivers alongside existing resources. Tailored policies should be designed, formulated, and implemented to facilitate the conversion of old and new growth drivers according to local conditions. Additionally, efforts should be made to maximize the influence and linkage effects of the basin's central cities.

In September 2024, Yellow River Conservancy Commission carried out a joint sediment discharge operation on key reservoirs in the upper and middle reaches of the Yellow River, including Longyangxia, Liujiaxia and Wanjiashan. The operation lasted for 16 days and achieved good results in sediment discharge and silt reduction. The five reservoirs of Shapotou, Qingtongxia, Haibowan, Wanjiazhai and Longkou discharged a total of 152.61 million tons of sediment, and the total erosion in the reservoir area was 66.92 million tons, with a combined sediment discharge ratio of 178.1%. The front sections of the Qingtongxia and Haibowan reservoir dams had been severely scoured, providing favorable boundary conditions for sediment reduction in the future. The Wanjiazhai Reservoir had achieved an annual equilibrium between sediment erosion and deposition, thereby effectively slowing the reservoir’s sedimentation rate. The aforementioned analysis demonstrates that utilizing upstream reservoir water storage to implement joint sediment discharge is not only effective but also offers a novel approach for reducing reservoir sedimentation during flat low-water years.

After the operation of reservoir impounding and sediment retention, it will cause the downstream river channel to be eroded and cut down, and even change the river pattern, which will have a certain impact on the safety of water-related projects. In order to master the rules of river sediment erosion downstream the reservoir, based on the water and sediment as well as cross-sectional observation data since the application of the Xiaolangdi Reservoir for sediment control, this paper analyzed the cumulative scouring volume, average scouring depth, the maximum water depth and the morphological changes of longitudinal and cross-sectional sections of the lower reaches of the river, and studied the influence of water and sediment and boundary conditions on scouring efficiency. The results show that from October 1999 to October 2022, the downstream river channel has accumulated a total of 2.276 billion m3 of erosion, showing the characteristics of “more erosion at the upper and less at the lower and uneven distribution along the course”. Among them, 70% occurs above Gaocun and 30% below Gaocun. The longitudinal gradient of the river channel increases in the upper and lower sections, while it decreases in the middle section, making the entire longitudinal profile more concave. The river channel has undergone significant widening and downward cutting. The increase in river width is larger at the top and smaller at the bottom, while the increase in water depth is smaller at the top and larger at the bottom. The riverbed has coarsened, with the median particle size increasing by 6% to 79%, and the scouring efficiency of the river channel has significantly decreased. The channel erosion efficiency below the reservoir is closely related to the average flood flow and the cumulative erosion volume in the preceding period. When the accumulative erosion volume above Huayuankou reach reaches 0.6 billion t and the discharge is 2 000 m3/s, the future erosion efficiency will be reduced to -2.9 kg/m3.

In order to explore the influence mechanism of new quality productivity to the carbon emissions in the Yellow River Basin, and then provide references for developing new quality productivity and promoting carbon reduction and emission reduction in the Yellow River Basin, this paper took 2013-2022 as the study period and nine provinces in the Yellow River Basin as the measurement unit, and used the entropy method to measure the development level of new quality productivity according to the three indicators of labor force, labor object and labor data. Furthermore, the direct impact of new quality productivity on carbon emissions was tested empirically by using the fixed effect model of individual and time factors, and the robustness test was conducted. The mechanism of influence of new quality productivity to the carbon emissions was tested empirically with the level of industrial structure upgrading and green technology innovation as the intermediary variable, and the level of market integration and the target of economic growth as the moderating variable. The results show that a) the development of new quality productivity has a significant inhibitory effect on carbon emissions in the nine provinces of the Yellow River Basin. b) New quality productivity reduces carbon emissions by improving the level of green technology innovation and industrial structure upgrading. c) Excessive economic growth target will increase carbon emissions and weaken the carbon reduction effect of new quality productivity, while the improvement of market integration level will reduce carbon emissions and enhance the carbon reduction effect of new quality productivity. Suggestions: Further improve the institutional mechanisms for the development of new quality productivity, continue to strengthen support for enterprises' green innovation and further optimize the industrial structure, so as to enhance the carbon reduction and emission reduction effect of new quality productivity.

Given the significant implications of the dynamic hydrological characteristics of the Bosten Lake Basin for regional water resources management, ecological preservation, and socio-economic activities, this study undertook an in-depth investigation into the fluctuations in precipitation, water surface evaporation, and drought index within the basin spanning from 1955 to 2020. Through the comprehensive application of diverse statistical methodologies, including trend analysis, cluster analysis, mutation detection, and wavelet analysis, this research unveiled the evolutionary patterns and potential trends in precipitation, evaporation, and drought index within the study area. The findings reveal that the Bosten Lake Basin falls into an extremely arid zone, where precipitation demonstrates significant interannual variability alongside a non-significant upward trend. Such variation patterns persist across multiple temporal scales, with the most prominent periodic oscillations observed at 10-20 year cycles. The abrupt change of evaporation mainly occurs around 2000, showing a periodic variation trend across multiple time scales, with the main variation cycle being approximately 40 years. While the drought index exhibits no statistically significant overall variation during the study period, it displays distinct periodic characteristics at decadal (10 year) and tridecadal (30 year) scales. Ultimately, the research outcomes not only elucidate the intricate change characteristics and potential trends of precipitation, evaporation, and drought index in the Bosten Lake Basin, but also furnish a robust scientific foundation and decision-making support for water resources management, ecological preservation, and drought relief and mitigation strategies within the basin.

In order to understand the current situation of extreme precipitation events in Henan Province, scientifically recognize and master the spatial-temporal evolution characteristics of extreme precipitation events, and provide basic information support for flood and drought disaster prevention and extreme precipitation event early warning, based on the precipitation data of 26 meteorological stations near Henan Province from 1973 to 2023, an extreme precipitation threshold standard was established to screen extreme precipitation events. Meanwhile, in combination with the recommendations of the World Meteorological Organization (WMO), indicators such as extreme precipitation and continuous wet period CWD were selected. The spatial-temporal distribution of extreme precipitation indicators was statistically analyzed by using M-K trend analysis, and the period was studied by using the wavelet function. The results show that in terms of spatial distribution, the extreme precipitation threshold and eight extreme precipitation indicators in Henan Province gradually increase from northwest to southeast, but the number of extreme precipitation days and the intensity of extreme precipitation do not have obvious spatial distribution characteristics. During the time series changes, among the 8 extreme precipitation indicators, except for the continuous wet period CWD, the number of heavy rain days R25, and the number of heavy rain days R50, the remaining 5 indicators all show a decreasing trend, but they show an increasing trend after 2000. The extreme precipitation in Henan Province has periodic scale characteristics of 26-31, 16-20, and 8-11 years during the study period.

In order to accurately identify the leakage risks of Tanshan Reservoir under complex conditions, this study proposed a multi-method integrated leakage detection framework. It combined various detection techniques, including the simulated flow field method, geophysical methods (such as high-density resistivity, transient electromagnetic, and ground-penetrating radar), and tracer techniques, along with geological surveys for comprehensive analysis. The study results indicate that the leakage mainly occurs through fractures in the dam foundation rock from the reservoir interior to the downstream, eventually emerging at the stone masonry sidewall of the energy dissipation basin. The main leakage channel lies within the completely weathered limestone layer beneath the dam body. The integrated leakage detection approach proposed in this study-revealing the overall leakage distribution through the simulated flow field method, identifying water-rich and high-moisture zones using geophysical methods, and determining leakage sources and paths with tracer techniques-can provide a reference for detecting similar complex leakages and offers technical support for emergency response and reinforcement efforts.

The Xiaolangdi Reservoir is a key project for controlling water and sediment of the Yellow River. Studying its sediment discharge law and regulation indicators is of great significance for maintaining effective storage capacity in the long term. Based on the analysis of measured data and the practice of water and sediment regulation, 34 sediment discharge processes in the Xiaolangdi Reservoir from 2010 to 2023 were selected, and the reservoir sediment discharge law and its influencing factors were analyzed, in the meantime the regulation indicators which were useful to reducing reservoir silt were proposed. The results show that, during water and sediment regulation in pre-flood season, sediment discharge is mainly caused by flushing of clear water discharged by the Sanmenxia Reservoir. The sediment discharge amount is positively linear correlated with the inflow volume and negatively linear correlated with the storage volume of the Xiaolangdi Reservoir. During water and sediment regulation in flood season, the sediment discharge ratio is negatively correlated with the degree of reservoir damming and the ratio of inflow and outflow flow, which is a power function relationship. The quantitative expressions of sediment discharge amount during water and sediment regulation in pre-flood season and sediment discharge ratio during water and sediment regulation in flood season are established, and the water level of the reservoir can be reduced and then maintained to 215 m and 223 m respectively during water and sediment regulation in pre-flood and flood season are proposed, in which the annual sediment discharge ratio can reach 125%.