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 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.

Most of the provinces (autonomous regions) along the Yellow River Basin face challenges such as fragile eco-environment, underdeveloped economies and imbalanced industrial structures, making carbon peaking particularly difficult. In order to explore effective and feasible pathways for carbon peaking and provide references for formulating carbon emission policies in the Yellow River Basin, this study, based on the 14th Five-Year Plan for economic and social development and the long-term goals for 2035 of the nine provinces (autonomous regions), established the three development scenarios of a low-carbon development mode prioritizing green growth and balancing economic progress with ecological protection, a baseline development mode continuing current economic trends, and a high-growth development mode focusing on rapid economic expansion without energy-saving or emission-reduction targets. Using panel data from 2000-2021 on per capita GDP, energy intensity, urbanization rate, population size and industrial structure, a Quantile Regression Neural Network (QRNN) model was applied for empirical analysis and the Gaussian kernel function was adopted for kernel density estimation and the probability prediction of carbon emissions from 2022 to 2035. The results show that a) under all three scenarios, Henan, Inner Mongolia and Qinghai have achieved early carbon peaking (in 2011, 2020 and 2013 respectively), while the other six provinces (autonomous regions) are unlikely to achieve carbon peaking on schedule (among which Shanxi is expected to reach carbon peaking by 2035). b) Qinghai and Shandong are suitable for the benchmark development mode, Inner Mongolia, Shanxi, Sichuan and Shaanxi are suitable for the low-carbon development mode and Henan, Gansu and Ningxia are suitable for the high-growth development mode. It is suggested to formulate differentiated development policies, establish a regional carbon trading market and a linkage mechanism for pollution control in the Yellow River Basin, and promote overall carbon reduction and emission reduction in the Yellow River Basin.

The fundamental solution to the management of the Yellow River lies in sediment control. In order to examine the practical predicament of the legal rules for sediment prevention and control in the Yellow River Basin and put forward suggestions for optimizing the path, this paper conducted a normative analysis of national legislations such as the “Yellow River Protection Law of the People's Republic of China” and the “Law of the People's Republic of China on Prevention and Control of Desertification” as well as the local legislations promulgated by provinces and autonomous regions along the Yellow River which was related to the protection of the Yellow River. It was pointed out that there were issues such as the dispersion of legal rules for sediment prevention and control affecting the realization of legislative quality and efficiency, the principle of “not conflicting” with national legislation restricting the development of local legislative content, and the differences in local rules hindering the realization of fairness in river basins. Based on the existing issues, the optimization paths are proposed: Optimizing the legal rule system for sediment prevention and control in the Yellow River Basin, promoting the effective supply of legislation, advancing regional collaborative legislation, enhancing the scientific nature of legislation, adhering to the concept of harmony between humans and sediment, and strengthening the operability of legal rules

In view of the issues existing in the current research on runoff evolution in the Aksu River basin, such as a single time-scale and insufficient consideration of the sensitivity of sequence length, a variety of methods such as Mann-Kendall trend test, Theil-Sen Median trend estimation, Pettitt mutation test and wavelet analysis were adopted to systematically study the runoff evolution laws of the main and tributary streams in this basin at different time scales such as inter-annual, intra-annual and flood events. The results show that the annual runoff of the Taushgan River, Aksu New River and Tailan River increase gradually, while the change of the Kumarak River is not obvious. The periodic oscillation of the four rivers is the most obvious on the 35-year, 55-year, 35-year and 55-year timescale, and the corresponding periods are 21-23 years, 32-35 years, 19-25 years and 36 years respectively. The annual distribution of runoff in the Aksu River basin is uneven, the runoff is larger in summer and autumn, and smaller in winter and spring, and the concentrated period is from June to August. The annual maximum flood peak discharge of the mainstream and tributaries fluctuate greatly, mainly concentrate in July and August. The key periods for flood control are July-September, April-August, July-August and July respectively. The tendency, mutability and periodicity analysis results of the runoff in the Aksu River watershed are all affected by the length of time series.

In order to deeply explore the characteristics and driving factors of runoff changes in the Shiyang River basin, and provide a scientific basis for basin management planning and ecological environment building, this study utilized the runoff data from 1956 to 2019 and applied mathematical statistics to analyze the runoff characteristics, in conjunction with meteorological data to assess the impact of climate change on runoff. The findings reveal that a) a decreasing trend in runoff volumes for the Gulang River, Huangyang River, Zamu River and Jinta River, while the runoff of Dajing River and Xiyang River remains relatively stable. b) The basin exhibits periodic changes over 2 to 10 years and 10 to 30 years. c) Apart from the Dongda River and Xida River, which lack significant abrupt change years, other rivers in the basin have notable abrupt changes in runoff between 1970 and 1990. d) The precipitation variation trends in the Shiyang River Basin are not significant, while the temperature has significantly increased. e) Based on the division of change points, the runoff reduction between the baseline and the change period ranges from 13.78% to 37.43%, with human activities identified as the key factor causing runoff reduction and changes.

Since 2019, during the regulation and operation of Liujiaxia Hydropower Station, it has been found that when the reservoir water level is below 1 723 meters, the sediment content passing through the turbine increases due to the scouring of the Taohe River channel, resulting in a sudden increase in the sediment content passing through the turbine, which seriously affects the safety of the generating units. At present, there are still relatively few studies on the correlation between sediment concentration in the passing water and reservoir operation indicators in China. In order to identify the main indicators causing the increase in sediment concentration, the main factors affecting the change in sediment concentration were analyzed through real-time data analysis and Pearson correlation coefficient analysis. These factors included water level, flow and velocity. Based on this, different dam front water level and inflow and outflow schemes were set up according to the actual operation of the reservoir. The RSS two-dimensional mathematical model was used to calculate the sediment concentration in front of the dam under different schemes, and suggestions for the operation and scheduling of Liujiaxia Reservoir were proposed. When the inflow is no more than 2 000 m³/s, the dam front water level can be operated at no less than 1 722 meters to control the sediment concentration. When the inflow further increases, in order to ensure the safe operation of the turbines, the dam front water level can be maintained at no less than 1 725 meters during operation.

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.

At present, cross-regional disasters occur frequently, and emergency cooperation is an important means of disaster prevention and reduction. In order to promote cross-regional emergency cooperation and improve emergency response capacity, this study took 18 cities in the upper reaches of the Yellow River as examples. Firstly, pre-causal conditions for cross-regional disaster emergency cooperation were selected from three aspects of internal attributes, network relations and external environment. Then, NCA method was used to analyze the necessity of the pre-causal conditions. The results show that the economic level, administrative level and geographical location are the necessary conditions to realize cross-regional disaster emergency cooperation. With the improvement of the level of pre-causal conditions, cross-regional disaster emergency cooperation is easier to achieve. There are three kinds of implementation paths of cross-regional disaster emergency cooperation: network relationship and external environment bidirectional driving, external environment leading and internal attribute leading logic driving. Therefore, this paper puts forward the suggestions for strengthening economic construction, promoting economic exchanges, deepening self-cognition and implementing measures according to local conditions.

In order to explore the trend of changes in water resources utilization efficiency during the transformation and development process of resources-rich regions and its inherent relationship with industrial structural transformation, this article combined Shannon entropy theory and traditional DEA model to measure the water resources utilization efficiency of resources-rich regions from 2007 to 2021.The interactive response relationship between industrial structure and water resources utilization efficiency was discussed by building the VAR model. The conclusions are as follows: The overall utilization of water resources in resources-rich regions is in a state of DEA inefficiency, with a range of water resources utilization efficiency of 0.572 and significant regional differences. There is a pulse response relationship between industrial structure and water resources utilization efficiency, and the transformation of industrial structure has a certain driving effect on water resources utilization efficiency. Within the research area, the impact of industrial structural transformation on water resources utilization efficiency tends to increase in Jiangxi, Inner Mongolia, Xinjiang and Heilongjiang, while the impact on other provinces is decreasing or even disappears.

In order to master the spatial-temporal changes and its driving factors of water conservation capacity in the Yiluo River basin, this paper adopted the InVEST model and water conservation calculation methods to quantitatively assess the water conservation capacity in the Yiluo River basin from 2005 to 2020. It analyzed the spatial-temporal variation characteristics and quantitatively examined the driving factors of water conservation function by using geographic detectors. The results show that a) from 2005 to 2020, the water conservation capacity in the Yiluo River basin shows a trend of initial decrease followed by an increase. The highest water conservation capacity is observed in 2005, while the lowest is in 2015. b) The southern and western mountainous areas exhibit stronger water conservation capacity, whereas the central, northern and eastern regions are relatively weaker. c) During the study period, the ranking of water conservation capacity across different land use types from strongest to weakest is grassland, forest, shrubland, construction land, farmland, unused land and water bodies, with densely vegetated areas demonstrating stronger water conservation capacity. d) Precipitation is identified as the primary factor influencing changes in water conservation capacity in the Yiluo River basin, and the interaction between precipitation and land use has the most significant impact on water conservation capacity.

Water scarcity has become a critical constraint on the sustainable development of China's economy and society. Emerging productive force, referred to as a new-quality productive force (NQPF), has become a key driver in enhancing resources use efficiency and promoting high-quality development. This study utilized panel data from 18 provincially administered cities in Henan Province from 2013 to 2022 to evaluate industrial water use efficiency and its driving effects by using DEA-Malmquist model. A comprehensive index system encompassing technological, green and digital productivity was built to represent NQPF, and its overall level was assessed through the entropy-weighted TOPSIS method. Furthermore, a Tobit regression model was employed to empirically examine the impact of NQPF on green industrial water use efficiency. The results show that a) the green industrial water use efficiency in Henan Province has shown an overall upward trend, but significant disparities exist across cities, indicating considerable room for improvement. b) Allocation and scale efficiency are the main contributors to total factor productivity growth in green industrial water use, while technological progress and pure technical change remain limiting factors. c) During the research period, the NQPF indices of all provincially administered cities in Henan Province show an increasing trend. Among them, Zhengzhou has the largest new quality productivity index, followed by Luoyang, and Jiyuan has the smallest. d) NQPF and per Capita GDP have significant positive effects on green industrial water use efficiency, and the proportion of industrial added value also has a positive impact on the efficiency of industrial water use. The study suggests vigorously promoting technological progress in industrial water-saving, enhancing management and technical capacity, optimizing water resources allocation to improve scale and allocation efficiency, and accelerating the development of NQPF to achieve coordinated progress between industrial water use and economic growth.

Identifying the variations and controlling factors of groundwater levels is very crucial to evaluate the effects of groundwater exploitation reduction (GWER), and it is an important prerequisite for accurately predicting the evolution of groundwater levels in the area of GWER. This paper selected the eastern plain of Handan as the study area, which was a pilot area of GWER in Hebei Province. Wavelet analysis, statistics and GIS methods were jointly used to analyze the spatial-temporal variations and controlling factors of shallow groundwater (SGW) and deep confined groundwater (DGW) levels during the years from 2018 to 2021. The results show that the annual head fluctuation range of SGW is from 0.9 to 7.3 m, and the annual head fluctuation of DGW varies from 2.8 to 17.6 m. The water level reaches to the bottom in July and reaches to the peak in December. The water levels in most areas show a rising trend in both SGW (0.8-4.6 m) and DGW (0.6-6.3 m). The depression cone areas for SGW and DGW are enlarged in dry seasons (SGW is 347.9 km² and DGW is 60.6 km²) and are reduced in wet seasons ((SGW is 91 km² and DGW is 516.2 km²). The water-level changes in SGW are closely related to precipitation, with a lag time of 141 to 224 days. The water diversion from the Yangtze River and the Yellow River, aiming to replace groundwater exploitation for industrial and domestic use as well as agricultural irrigation, has contributed to the reduction of groundwater pumping, and thereby boosted the recovery of water levels in this region.

Under the combined influences of global climate change, evolving underlying surface conditions, and anthropogenic activities, the hydrological-sediment regimes of the Yellow River Basin have undergone notable modifications in recent decades. These alterations have consequently driven adaptive transformations in fluvial landscapes, including waterfall systems. As a natural waterfall formed along the mainstem of the Yellow River within the Jin-Shaan Grand Canyon, Hukou Waterfall serves as a critical study target. Leveraging long-term continuous in-situ monitoring data, field investigations, and historical archives, this research systematically investigated the primary landscape characteristics of Hukou Waterfall-encompassing morphology, scale, and coloration, while elucidating its interactive relationships with reach-scale hydrological and sediment dynamics. Furthermore, an analysis of the waterfall's historical evolution from 1956 to 2023 reveals two key findings: a progressive reduction in overall scale since 1956, and a significant increase in the occurrence frequency of clear-water flow events.

The Danjiangkou Reservoir serves as the water source for the South-to-North Water Diversion Project and is designated as a national-level water source protection area. The water quality of the reservoir is critical to the water safety of downstream regions and the urban and rural populations along the South-to-North Water Diversion Project. Utilizing 49 GF-1 satellite remote sensing images of the Danjiangkou Reservoir from 2020 to 2024 as data sources, and incorporating turbidity data obtained from national control monitoring stations, this study systematically compared and analyzed the inversion accuracy of turbidity by using linear regression, multiple linear regression, XGBoost, random forest and Generalized Regression Neural Network (GRNN) models. The results demonstrate that the GRNN model exhibits a significant advantage in turbidity inversion. The GRNN model is subsequently applied to rebuild the turbidity distribution in the Danjiangkou Reservoir over different time periods. The findings indicate that: the turbidity in the study area is generally low, predominantly below 15 NTU, and its distribution follows a Gaussian distribution with a mean (μ) of 3.13 NTU and a standard deviation (σ) of ±1.12 NTU. Temporally, turbidity values fluctuate, with peaks observed during the winter months. Spatially, localized increases in turbidity are evident in the southwest and northwest regions, influenced by anthropogenic activities and precipitation.

In order to enrich the research on Net Primary Productivity (NPP) and provide insights for the ecological sustainability and carbon sink enhancement of the Yellow River Basin, this study investigated the temporal and spatial patterns of NPP from 2000 to 2020. The basin was divided into three ecological zones of the semi-arid region of the mid-temperate zone (Zone I), the semi-humid region of the warm temperate zone (Zone Ⅱ) and the semi-arid region of the plateau zone (Zone Ⅲ). Based on multi-source remote sensing data, the Carnegie-Ames-Stanford Approach (CASA) model was used to estimate annual and monthly NPP values for the entire basin and its three sub-regions. To further interpret the impact of environmental factors, the Shapley additive explanations (SHAP) method was introduced to analyze the contributions of temperature, precipitation, NDVI and solar radiation to NPP variation. The main findings are as follows: a) Spatially, NPP shows significant heterogeneity, with higher values concentrated in Zone II and lower values widely distributed in ZonesⅠand Ⅲ. The mean NPP values rank as follows: Zone Ⅱ> Zone Ⅲ> Zone I. Areas along the Yellow River generally exhibit higher NPP than other areas at the same latitude. b) Temporally, NPP in the basin shows an overall upward trend with fluctuations and exhibits strong intra-annual seasonality. During the study period, 47.17% of the area experiences an increase in NPP, while 3.33% shows a decrease. Zone Ⅱ experiences the most significant increase, and the growth rate of NPP gradually slows over time. c) At the basin scale, NDVI has the greatest influence on NPP, and its interaction with solar radiation is particularly strong. However, the dominant driving factors are varied by sub-region: NDVI in Zone I, air temperature in Zone II and NDVI again in Zone Ⅲ. d) The strategies for enhancing NPP in each ecological area of the Yellow River Basin should be adapted to local conditions, have their own focuses, and fully attach importance to the interaction effects among various natural factors.

The InVEST model was used to quantify the spatiotemporal distribution characteristics of water conservation in the urban agglomeration of the middle reaches of the Yellow River from 2000 to 2020. Geographic Detectors and Segmented Linear Regression were used to analyze the influencing factors of water conservation. Geographically and Temporally Weighted Regression (GTWR) model was used to explore the impact mechanism of natural environment and human activities on water conservation. The results show that: from 2000 to 2015, the spatial distribution of water retention capacity in the Middle Yellow River urban agglomeration exhibits a decreasing pattern from south to north, which shifts to a decline from both northern and southern ends toward the central region by 2020; Precipitation demonstrates the strongest explanatory power for water retention, and the explanatory power of dual-factor interactions is significantly higher than that of single factors; The mean threshold values for precipitation, temperature, and relative humidity are 628.26 mm, 14 °C, and 59.82%, respectively; Areas dominated by precipitation account for the largest proportion of regions influencing water retention changes, and dominant factors in other regions are gradually replaced by precipitation; The influence of natural environment on water retention decreases from south to north, and before 2015, regions dominated by human activities show a contraction in the east and expansion in the south, while after 2015, nearly all areas are predominantly dominated by natural environmental factors.

In order to reveal the reinforcement mechanisms of plant roots on loess slopes and provide a foundation for advancing theoretical research and practical applications of vegetative slope protection in the Loess Plateau region, this study focused on Robinia pseudoacacia, a prominent afforestation species in the area. Through the tensile testing of Robinia pseudoacacia roots and root-pull experiments on root-soil composites, we analyzed the tensile properties of roots of varying diameters and the factors influencing the root-soil friction coefficients. The findings indicate that a) the tensile strength of Robinia pseudoacacia roots exhibits a positive correlation with root diameter, whereas both the longitudinal ultimate elongation and elastic modulus demonstrate a negative correlation with increasing root diameter. b) Soil dry density significantly influences the root-soil friction coefficient, which increases as soil dry density rises. This phenomenon is attributed to the enhanced interlocking between roots and soil at higher densities. c) Conversely, the root-soil friction coefficient decreases with increasing soil moisture content, primarily due to the thickening of the water film on soil particles, which diminish the roughness and adhesive strength between the soil and roots. d) No significant relationship is observed between the root-soil friction coefficient and the thickness of roots of the same species, likely because the surface roughness of roots across different diameters does not vary substantially.

In order to study the spatial-temporal evolution characteristics of reference crop evapotranspiration (ET₀) and its response to climate change in Shaanxi Province, daily meteorological data in the past 1960-2017 were collected from 33 meteorological stations. ET₀ was calculated by using the FAO 56 PM formula. Sensitivity analysis and contribution rate were used to quantitatively identify the dominant factors affecting ET₀ changes. The results show that a) there is upward trend in the maximum and minimum air temperature, whereas, downward trend in the sunlight hours, wind speed and relative humidity. b) The average annual ET₀ in Shaanxi Province is 981 mm, and the trend of annual ET₀ is not significantly decreasing at -2.85 mm/10 a. The spatial distribution of annual average ET₀ shows a pattern of high in the north, low in the south, and high in the east and low in the west. c) The sensitivity of annual scale ET₀ to meteorological elements in Shaanxi Province is ranked from high to low as relative humidity, maximum temperature, sunshine hours, wind speed and minimum temperature. d) The contribution rates of meteorological elements to the annual scale ET₀ changes are wind speed, maximum temperature, sunshine hours, minimum temperature and relative humidity in Shaanxi Province from high to low. Therefore, the main controlling factor affecting the annual scale ET₀ changes in Shaanxi Province is wind speed.

Reservoir storage capacity is a key parameter influencing the accuracy of water and sediment regulation decisions and guaranteeing the safe operation of reservoirs. In light of the issues such as low efficiency and insufficient accuracy existing in traditional reservoir storage capacity calculation methods, a three-dimensional calculation method for reservoir storage capacity based on BIM technology was proposed. Based on the .NET framework and by employing the C# language for the secondary development of Revit, a three-dimensional calculation plug-in for reservoir storage capacity had been developed, enabling rapid calculation and three-dimensional display of reservoir storage capacity. The calculation results of this plug-in were compared with those obtained by the contour volume method and Global Mapper software to verify the calculation accuracy of the plug-in. The results indicate that this plug-in can realize the automatic calculation of reservoir storage capacity and the automatic drawing of reservoir characteristic curves. The average relative error between the storage capacity calculated by the plug-in and that obtained by the contour volume method is 3.03%, and the average relative error between the storage capacity calculated by the plug-in and that obtained by Global Mapper software is 0.15%. The calculation results of the plug-in are reliable, and this plug-in can be used as a new tool for reservoir storage capacity calculation.

In order to ensure the stable and compliant operation and energy conservation and consumption reduction of a sewage treatment plant in a certain town in Shanxi Province under seasonal changes, a multi-stage AAO process simulation model was built by using the ASM2D model and WEST software. It selected process operating parameters internal reflux ratio, external reflux ratio, DO concentration, water inflow ratio and SRT for single factor analysis first, clarified the impact of various parameters on the removal of effluent pollutants, and then used the five factor multi-level orthogonal experiments to obtain the optimal operating conditions for stable operation of sewage treatment plants in summer and winter seasons. The results show that when considering all five factors comprehensively, the optimal effluent effect is achieved in summer when internal reflux ratio is 150%, external reflux ratio is 50%, DO concentration is 1 mg/L, influent ratio is 3:1 and SRT is 15 days. Compare with the original plan, the simulated effluent TN removal rate increases by 14.61%, the aeration rate of the aerobic tank is reduced by 66.67%, and the internal and external reflux rates are reduced by 62.50% and 50% respectively. In winter, the optimal effluent effect is achieved when internal reflux ratio is 250%, external reflux ratio is 80%, DO concentration is 2 mg/L, inflow ratio is 1:2 and SRT is 20 days. Compare with the original plan, the simulated effluent TN and TP removal rates increase by 2.47% and 3.46% respectively, and the aeration rate is reduced by 33.33%, the internal and external reflux rates decrease by 62.50% and 20% respectively. After optimizing the operation plan, the effluent quality of the plant has been improved, achieving the goals of stable operation and energy conservation and consumption reduction.

In order to explore the mechanical response of prestressed double-layer lining structure during the construction and operation of water conveyance shield tunnel, taking the Pearl River Delta Water Resources Allocation Project as an example, a three-dimensional calculation model of double-layer lining structure was established by finite element numerical simulation method, and the bearing capacity characteristics of double-layer lining structure with or without prestress were analyzed. The results show that when the internal water pressure does not exceed 0.9 MPa, the ordinary double-layer lining structure can meet the safety requirements and does not need to apply prestress. When the internal water pressure is too large, it is necessary to apply prestress to the double-layer lining structure to give full play to its bearing capacity. Compared with the pre-stressed tension stage, the coordinated bearing capacity of the segment lining and the pre-stressed lining is stronger and the contact pressure is more fully transmitted in the water-filled operation stage. During the whole construction and operation stages, the displacement variation of the double-layer lining structure is small, and it has a good working state.

The banks of the Dongzhuang Reservoir area of the Jinghe River are crisscrossed with gullies and have a deep loess cover. After the reservoir area is filled with water, the fluctuation of water level will increase the probability of deformation and instability of new reservoir banks and the revival of ancient landslides. Based on the geological conditions of Dongzhuang Reservoir area, three typical water-related landslides with high risk (Hejia, Jiaojiahe and Fengjia) were selected for the analysis of the causes of landslides and the distribution characteristics of landslides. The coupling mechanism between landslide deformation and water level fluctuation after water storage were analyzed by establishing numerical models. The results show that there are three higher-risk water-related landslides and they are typical loess-bedrock landslides within the 30 loess landslides in the reservoir area. The stability of loess landslides along the bank of the reservoir is affected by the fluctuation of reservoir water level. The gradual decline of reservoir water level and the long-term maintenance of high water level will lead to the reduction of the safety coefficient of the landslides. The faster the rate of decline of reservoir water level, the faster the safety coefficient of the landslides decreases to the minimum value. The possibility of overall large-scale sliding of loess landslides in the reservoir area is low. Conversely, the risk of instability of the leading edge slides is relatively high when the water level drops.

Foam lightweight soil is important filler for road embankment, but there are problems such as large dry shrinkage deformation and insufficient strength of large volume foam lightweight soil. Foam lightweight soil was produced by using silt soil from the lower reaches of the Yellow River as fine aggregate. The effects of silt soil content under different design wet densities on the flow value, compressive strength, dry shrinkage rate and durability were analyzed through experiments, and the relationship between its microstructure and mechanical properties was analyzed through numerical simulation. The results show that as the silt soil content increases, the 28-day compressive strength of foamed lightweight soil decreases. According to the existing specifications, combined with engineering examples and test results, foam lightweight soil is recommended as the sub-grade filler. The mixing ratio of silt soil is 20%-30%, and the dry shrinkage rate of foam lightweight soil decreases with the increase of the mixing ratio of silt soil. Observing the microstructure, it is found that the addition of silt soil can expand the pore distribution range of lightweight soil.