[Objective] In recent years, extreme precipitation events occurring in changing environments have become increasingly frequent, and the assumption of stationary in traditional frequency analysis has been gradually questioned. Therefore, it is necessary to reasonably analyze the non-stationary characteristics of extreme precipitation in the basin, which will help to dynamically assess the risk of rainstorm and improve the disaster prevention and mitigation capacity of the basin. [Methods] Based on the GAMLSS model, a time-varying distribution model with time as the explanatory variable is established for the extreme precipitation frequency index and intensity index of 82 meteorological stations in the upper reaches of the Yangtze River Basin. Then, the Mann Kendall method is used to analyze the trend of the extreme precipitation frequency index and intensity index series, and the disaster causing effect of extreme precipitation in the upper reaches of the Yangtze River Basin is evaluated.[Results] The result indicate that:(1) the extreme precipitation index of most stations in the upper reaches of the Yangtze River basin exhibits non-stationary characteristics. Among them, more than 70% of stations have non-stationary characteristics for moderate rain days R10 and total rainfall PRCPTOT, over 40% have non-stationary characteristics for heavy rain days R25,heavy rainfall R95P, and extreme daily rainfall RX1day, and about 13% have non-stationary characteristics for extremely heavy rainfall R99p;(2) The proportion of stations with significantly increasing distribution parameter sequences of extreme precipitation frequency and intensity index in the GAMLSS optimal model is 20/82 and 36/82, respectively. [Conclusion] The frequency of extreme precipitation in the middle and upper reaches of the Yibin to Yichang section will increase in the future; the intensity of extreme precipitation in the central region of the upper reaches of the Yangtze River will increase in the future; the frequency and intensity of extreme precipitation in the border areas below Shigu in the Jinsha River and the middle and lower reaches of the Mintuo River Basin will increase in the future. Compared to simple trend analysis, time-varying distribution models can diagnose the non-stationary characteristics of sequences in more detail.

[Objective] In recent years, urban areas have experienced frequent flooding, posing significant threats to public safety. The evacuation of residents from flooded roads and buildings, both before and during disasters, is critical as it directly influences the severity and aftermath of the disaster. [Methods] A comprehensive review of recent studies on flood evacuation was conducted, focusing on four key areas: flood evacuation risks, characteristics of human behavior, the impact of the built environment, and numerical simulations. [Results] The risk assessment of flood evacuation has established a preliminary foundation, yet discrepancies between research and real-world scenarios, along with the lack of standardized criteria, remain significant challenges. Evacuation behavior has been studied through risk assessments and route planning, while subjective behavior has been summarized from empirical data and video analysis. Research on the impact of architectural elements on evacuation, beyond shelters and staircases, is notably insufficient. While current evacuation models can simulate behaviors in simple scenarios, there is still a need for optimization in modeling complex behaviors, architectural features, and evacuation modes. [Conclusion ]Future research should integrate deep learning, big data, and other emerging technologies with experimental and simulation-based approaches to enhance flood evacuation risk control and human behavior studies. Both qualitative and quantitative analyses of various architectural factors' facilitating or hindering roles in the evacuation process are necessary. Finally, efforts should be made to translate research findings between the study of evacuation characteristics and simulation practices.

[Objective] The particle swarm optimization algorithm is widely used in research fields such as inverse problem solving, function optimization, data mining, and machine learning, but it still faces the problem of premature convergence when solving complex multimodal problems. In order to improve the speed and accuracy of traditional particle swarm optimization in handling complex multimodal problems, this paper proposes the Fast Comprehensive Learning Particle Swarm Optimization algorithm( FCLPSO). [Methods] The FCLPSO algorithm introduces three attributes: learning probability curve, presonal probability, and group influence probability, to characterize the different learning abilities of each individual particle. At the same time, strategies such as reinforcement learning and particle rebirth are added to improve the convergence speed of the algorithm and monitor and jump out of the " pseudo convergence" state. 14 standard benchmark test functions and 6 commonly used particle swarm optimization variant algorithms were selected for performance analysis of the FCLPSO algorithm. [Results] The result showed that in terms of convergence, the average ranking of the FCLPSO algorithm was 1. 86, with 7 times ranking first, 2 times ranking second, and 0 times ranking last and the overall ranking was first; In terms of robustness, the FCLPSO algorithm ranks first with an average success rate of 94. 3%, and the lowest success rate among the 14 test functions is 73. 3%; The minimum number of fitness evaluations required to reach the threshold is 40817, which is half the number of evaluations compared to other algorithms. [Conclusion] The result indicate that the FCLPSO algorithm ranks first in terms of convergence accuracy, convergence speed, and robustness, and has more advantages in solving complex multimodal problems. It can provide an important means for solving complex optimization problems in engineering applications.

[Objective] In order to solve the problem that the low temporal resolution and high spectral heterogeneity of remote sensing images in flood monitoring in arid areas of northwest China lead to low recognition accuracy of flood areas and inability to extract more detailed flood change information, a flood area recognition and change monitoring method based on spatial-spectral feature fusion and multi-source heterogeneous remote sensing images correlation analysis is proposed. [Methods] Taking the flood event in Sarhusong Township, Altay Prefecture, Xinjiang as an example, seven temporal multispectral images of Landsat8, HJ-1A, Sentinel-2A and GF-1 before and after the flood event are obtained. Then multi-dimensional feature vectors, including water index(NDWI, NDMBWI, WI2021) of image spectral reflectance, entropy, homogeneity texture features and as well as are extracted from them. PCA technology is used to reduce feature dimension; Finally, the random forest(RF) classifier is used to fuse multi-dimensional spatial-spectral features so as to identify water bodies and to recognize the flooding areas from remote sensing images acquired in every periods. After comparing the water body recognition result of adjacent temporal images, the dynamic change information of flood submerged areas is obtain. [Results] Through experimental verification, the result indicate that the false alarm rates for water extraction from Landsat images are 0. 21%, 0. 28%, and 0. 32%, with corresponding the miss rates of 2. 17%, 3. 37%, and 0. 110%. The maximum flooded area is 355. 1 km², with submerged farmland and grassland covering areas of 134. 3 km² and 229. 2 km², respectively. [Conclusion] The following conclusion can be obtained that the RF recognition algorithm with PCA for multi-feature fusion significantly improves the low recognition accuracy of scattered water bodies in single temporal Landsat8 images, and the overall accuracy of water body recognition is 13. 7%, 10. 8% and 2. 03%, higher than that of NDWI water body index method; The use of multi-source remote sensing image data makes the monitoring cycle as short as 1 week, which makes the extracted flood evolution process information more detailed and makes up for the shortage of satellite transit time; In addition, the remote sensing monitoring result of flood dynamic changes are basically consistent with the development trend of meteorological and hydrological observation data. Through the identification and change monitoring of flood water bodies in Sarhusong Township, it is fully demonstrated that in semi-arid areas, multi-source optical remote sensing images can effectively identify flooded areas, providing important data support for emergency disaster relief.

[Objective] Flash floods often contain floating debris such as driftwood and branches, which can cause bridge blockages, affecting the river' s flood-carrying capacity and increasing the risk of flash flood disasters. Existing standards for evaluating the risk of flash flood disasters don' t consider the impact of bridge blockages, underestimating the risk level.[Methods] takes A river channel in Huachi County, Gansu Province was took as an example, and a three-dimensional hydrodynamic numerical model was used to carry out research on the flood inundation risk under different bridge blockage rates.It analyzed the impact of different design rainstorm conditions such as 100-year, 50-year, 20-year, and 10-year return periods, as well as the bridge blockage rate on the flood risk. [Results] The research indicates that under no blockage conditions, the river's flood prevention capacity is greater than a 50-year return period flood. However, as the blockage rate increases, the floodwater level in the river rises. Notably, when the blockage rate reaches 80%, the bridge's flow capacity coefficient under a 50-year return period flood decreases by 60%, and under a 10-year return period flood, it decreases by 22%. An empirical relationship between the bridge's flow capacity correction coefficient and the blockage rate has been established. [Conclusion] Bridge blockages significantly reduce the river's flood-carrying capacity and increase the risk of flooding. In the assessment of flash flood disaster risk, it is necessary to consider the potential impact of bridge blockages. The empirical formula for the flow capacity correction coefficient proposed in this study can provide a reference for setting the boundary conditions within the bridge section under blockage conditions in a one-dimensional model.

[Objective] In recent decades, the impact of global warming has intensified, leading to significant changes in precipitation patterns and other climate factors across Yangtze-Huang-Huai-Hai River Basins. This has resulted in a rise in extreme precipitation events and an increase in the frequency of droughts and floods. To refine the understanding of precipitation levels, further analysis is needed to conduct a comprehensive analysis of long-term trends in rainfall intensity, changes in rainy days, and the influence of temperature, atmospheric circulation, and other meteorological factors on rainfall intensity within the basins. [Methods] Based on the daily observation data collected from 417 meteorological stations within the basin spanning from 1956 to 2022, various statistical analyses are employed, including linear slope analysis, the Mann-Kendall(M-K) trend test,Sen′s slope estimation, correlation analysis, and Morlet wavelet analysis, to comprehensively analyze the data. [Results] The results indicate that precipitation increases in the Yangtze River Basin(6. 12 mm/10 a), while decreasing in the Huang-HuaiHai River Basin(with reductions of -14. 64 mm/10 a,-3. 97 mm/10 a, and -6. 47 mm/10 a). Multiple types of time-scale main cycles of precipitation and rainy days exist. Regarding rainfall intensity, heavy rainfall and storm increase in the Yangtze River Basin(1. 03 mm/10 a, 7 mm/10 a), whereas the Huang-Huai-Hai River Basins experience a decrease in light, moderate,and heavy rainfall. Nearly 90% of stations in each basin exhibit a decreasing trend in various types of rainy days, with spatial correlation coefficients of rainfall intensity and corresponding rainy days mostly exceeding 0. 88. The interannual variation of mean and maximum(lowest) temperatures in the basin demonstrates a significant upward trend, correlating with rainfall intensity in each basin. [Conclusion] The results reveal that,(1) annual precipitation in each basin, alternating between abundance and depletion, exhibits an increasing trend in the Yangtze River Basin, while Huang-Huai-Hai River Basins experience decreases.The number of rainy days across the entire basin significantly decreases, with similar main cycles observed in rainfall intensity and rainy days.(2) Rainfall intensity and rainy days trends in each basin are consistent, with a high spatial correlation between them. Extreme precipitation events worsen due to increased heavy and storm rainfall in the middle and lower reaches of the Yangtze River, while decreases in light and moderate rainfall in the Huang-Huai-Hai River Basins lead to frequent drought events.(3) Warming affects rainfall intensity differently in each basin, primarily resulting in increased heavy rainfall in the Yangtze River basin and accelerating the decline of light rainfall in the Huang-Huai-Hai River Basins, exacerbating flooding in the south and drought in the north. Changes in atmospheric circulation factors, including AMO, EASMI, SCSSI, SASMI, and Nino3. 4, also influence extreme precipitation within the basin and drought events in North China by impacting atmospheric circulation, particularly monsoon intensity in East Asia, South Asia, and the South China Sea.

[Purpose]The land use change caused by climate change and human activities brings challenges to water resources regulation and management, which makes it a current research need to explore the hydrological simulation process under the influence of both and make quantitative prediction and analysis. [Methods] Based on three climate models of CMIP6, namely ACCESS-CM2, BCC-CSM2-MR, and Nor ESM2-LM, two concentration scenarios SSP245 and SSP585 were used to simulate the precipitation, minimum temperature, and maximum temperature of the Jinghe River Basin in the future period(2022—2044)after deviation correction; Based on the land use data of the watershed in 2005 and 2015, the CA-Markov model is used to predict the spatial distribution of land use in the watershed in 2025. Combined with climate model data, the SWAT distributed hydrological model is driven to predict future runoff changes in the Jinghe River Basin and analyze the impact of two factors on the rate of runoff change. [Results] The research result indicate that:(1) In the future period(2022—2044), under the SSP245 and SSP585 scenarios, the annual average precipitation will increase by 0. 3% and 1. 41% compared to the reference period(2006—2012), with the lowest temperature increasing by 0. 9 ℃ and 1. 11 ℃, and the highest temperature increasing by 0. 28 ℃ and 0. 07 ℃, respectively.(2) In 2025, the area of construction land and arable land increased by 34. 97% and 3. 15% respectively compared to 2005, while the area of grassland and forest land decreased by 4. 30% and 1. 59%.(3) The R² and NSE values of the simulated and measured runoff values during the reference period and validation period are 0. 86 and 0. 7,0. 76 and 0. 71, respectively, with R² greater than 0. 7 and NSE greater than 0. 65.(4) The simulated annual average runoff values for the four scenarios(S45_ LUC05, S85_ LUC05, S45_ LUC25, S85_LUC25) are 387 m³/s, 387. 87 m³/s, 419. 17 m³/s, and 422. 94 m³/s, respectively. [Conclusion] (1) In the future(2022—2044), the average annual precipitation and temperature in the Jinghe River Basin will show an overall upward trend.(2) In the future period(2025), the construction land area of the Jinghe River Basin will significantly increase, while the grassland and forest area will show a decreasing trend.(3) The SWAT model has good applicability in hydrological simulation of the Jinghe River Basin.(4) Under the four scenarios, future runoff will show an upward trend, Climate and land use change jointly affect runoff change, and the impact of land use change on runoff is greater than that of climate factors.

[Objective] In order to promote the popularization and dissemination of water efficiency labeling, and explores the adoption behavior for water efficiency labeling from the perspective of consumers, [Methods] based on the Motivation Theory and the Stimuli-Organism-Response( S-O-R) Model, the influence factors of consumers′ adoption behavior for water-efficiency labeling were analyzed by using the Grounded Theory, and the key influence indexes were identified by using the Random Forest Classifier, and the System Dynamics Model was constructed on this basis to simulate the dynamic evolution of consumers′adoption behavior for water efficiency labeling. [Results] The results show that: the evolution trend of adoption behavior in the simulation cycle can be divided into three stages, basically unchanged in the early stage, slowly rising in the middle stage, and rapidly rising in the late stage; the sensitivity of internal demands or external triggers to the motivation for adoption behavior is in the order of size: economic demands>psychological demands>group norms >marketing strategies; the sensitivity of individual factors to the level of adoption behavior is in the order of size: cognition degree > water-saving awareness > perceived trust >perceived value; the sensitivity of environmental factors to the level of adoption behavior is in the order of size: publicity and education>water-saving atmosphere. [Conclusion] The result indicate that: the level of consumers′ adoption behavior for water efficiency labeling shows a slow and then fast rising trend during the simulation period; economic demands are the key elements to stimulate consumers′ motivation for adoption behavior; cognition degree and publicity and education are the most important factors to influence consumers′ motivation for adoption behavior to be externalized into adoption behavior. The study reveals the dynamic evolution of consumers′ adoption behavior for water efficiency labeling, which can provide a theoretical basis for the design of promotion strategies and implementation paths.

[Objective] By introducing the “soil reservoir” analysis paradigm, the nature and types of soil reservoirs in the ecotone between desert and grassland were identified and summarized, which provided a basis for the engineering management of regional soil water resources and its application in ecological restoration. [Methods] Based on the distribution law and relationship between soil texture and soil water content at the regional scale, the concepts and connotations of “characteristic soil reservoirs” and “general soil reservoirs” in the desert-grassland ecotone(central Ningxia) were proposed and analyzed based on the depth and range of relative water enrichment in the soil profile from 0 to 200 cm. [Results] The result shows that:(1) At the regional scale, there is a negative linear regression relationship between the soil moisture content of 0~20 cm, 20~60 cm, 60~140 cm and 140~200 cm and the soil sand content of 0~30 cm soil layer, and the linear relationship between soil moisture content of 20~60 cm and soil sand content of 0~30 cm is the most significant(R²=-0. 23, P≤0. 05).(2) Indicated by the soil water content and the coefficient of variation, the characteristic depth of the soil profile of the characteristic soil reservoir is 20~140 cm(desertification group) and 20~60 cm(loam group), and there is no “characteristic soil reservoir” with a fixed location in the 0~200 cm soil layer of the sandy soil group.(3) The spatial distribution of soil moisture content and surface soil sand content in the 20~60 cm soil layer shows a rotational correspondence, which is potentially consistent with the distribution of the multi-year average isoprecipitation line in the study area, highlighting the indicative significance of “general soil reservoir” in the region. [Conclusion] Soil texture is the key factor to determine the relative enrichment degree and location of local soil moisture, that is, the occurrence of soil reservoirs. Precipitation and soil texture jointly determine the occurrence of soil reservoirs on a regional scale. The occurrence of soil reservoirs in the natural ecosystem of arid areas is essentially a process of precipitation redistribution with soil as the medium. It is manifested as a higher and relatively stable water content at a certain position in the vertical section of the soil, which plays a role in the conservation and regulation of uncertain precipitation resources in arid areas.

[Objective] Analyzing the runoff wetness-dryness encountering characteristics between water source and water receiving areas is essential for optimizing water diversion schemes and implementing engineering operational strategies in a timely manner. [Methods] Taking the Yangtze River to Huaihe River Diversion Project as an example, according to the monthly measured runoff data of Datong Station and Lutaizi Station from 1956 to 2022, the correlation coefficient, the standardized runoff index, as well as marginal distribution functions and joint probability distribution models based on two-dimensional Copula functions were employed, to describe the characteristics of runoff wetness-dryness for a single station and reveal the complementary patterns of two-dimensional runoff. [Results] The result indicated that weak correlations between these two stations across annual, high-flow and low-flow time scales, with Kendall correlation coefficients of 0. 216, 0. 273 and 0. 227,respectively. Datong Station experienced high-flow months from April to June, with corresponding probabilities of 0. 313, 0. 328and 0. 373; while Lutaizi Station encountered low-flow months in June and August, with probabilities of 0. 209 and 0. 179,respectively. It could also be shown that the sum of synchronous probabilities for runoff combinations were 54. 5%, 52. 5% and 52. 2% across annual, high-flow and low-flow time scales, respectively; and the probabilities of being favorable for transferring water from the source area to the receiving area were 72. 7%, 73. 7% and 73. 9% during these three time scales. [Conclusion] The conclusion were that the Gamma distribution could well fit the distribution characteristics of runoff under different time scales, and the optimal Copula functions for runoff combinations between these two stations were Frank Copula, Frank Copula and Clayton Copula across annual, high-flow and low-flow time scales. The sum of asynchronous probabilities for runoff combinations were all greater than the sum of synchronous probabilities under these time scales.

[Objective] In order to investigate the potential existence of karst water channels within the depression cone area, and to provide solutions for addressing collapse risks in karst regions and groundwater flow issues near inadequate waterproof or intermittent curtains, [Methods] taking the Panlong lead-zinc mine area in Guangxi as a case study, the theoretical value(difference)of the water level at the observation point is calculated using the descending funnel curve. By comparing and analyzing the differences between the theoretical and measured(difference) values, along with on-site drilling and collapse data, a prediction of the underground water channels in the karst region will be made. [Results] The result prove that the proposed method can accurately predict the karst water channel. [Conclusion] In a karst aquifer that forms a stable depression cone, when the measured water level of a borehole is lower than the theoretical value(h_Measure<h_Theory), or when the measured difference exceeds the theoretical difference(Δh_Measure>Δh_Theory), it indicates the presence of a karst water channel at the borehole. The concept of the landing funnel is introduced, suggesting that the relative aquifuge within the influence range of the funnel alters the horizontal distance of the measurement points outside the aquifuge. The adjusted distance should be represented as l+r. The diffraction characteristics of the cone of depression can indicate the presence of runoff channels within the adjacent aquifuge.</h

[Objective] The temporal stability of soil moisture in Haloxylon ammodendron plantations in desert regions was elucidated to provide a foundation for optimizing soil moisture monitoring and prediction. [Methods] Field-observed soil moisture content data from the 2023 growing season were analyzed using classical statistical and temporal stability analysis method. The spatiotemporal variability and temporal stability of soil moisture were investigated at depths of 0~400 cm in Haloxylon ammodendron plantations aged 5 to 25 years. Spearman rank correlation coefficients and relative differences were calculated to assess the temporal stability of soil moisture. [Results] Soil moisture content in the surface layer(0~100 cm) remained relatively stable across stand ages, maintaining high levels between 6% and 9%. In contrast, soil moisture content in the 100~400 cm layer significantly decreased with increasing stand age, exhibiting fluctuations ranging from 2% to 9%. Deeper soil layers showed greater variability than shallower layers. The spatial variability of soil moisture content increased with soil depth.Plantations younger than 10 years demonstrated high temporal stability of soil moisture(Spearman rank correlation coefficient >0. 8). Conversely, the temporal stability of soil moisture in deeper layers of older plantations(15 years, 20 years, and 25 years)was significantly reduced. [Conclusion] The dynamics of soil moisture in Haloxylon ammodendron plantations in desert regions are jointly influenced by stand age and soil depth. Overall, soil moisture content decreased with increasing stand age, primarily due to scarce precipitation, intense evaporation, and substantial water consumption through transpiration in the study area.Appropriate water management measures should be implemented in older plantations to ensure sustainable soil moisture use. New insights into the impact of artificial vegetation on soil moisture balance and ecosystem health are provided.

[Objective] Turbulent water flow caused by high-speed water flow is easy to cause the problem of induced vibration of hydraulic structures such as sluice pier. When the structural vibration is severe or the structural resonance is caused, it will seriously threaten the operation safety of the project and even cause structural damage. The spillway of a hydropower station was taken as an example to study the vibration characteristics of gate pier under the action of high-speed water flow, analyze the factors affecting the vibration of gate pier, and provide safety guarantee for the safe operation of the project, [Methods] Through the field test, the left and right gates are gradually opened to form a single hole, a double hole joint operation and other conditions to form high-speed water flow, and monitors the vibration of gate pier under each condition were tested. The vibration characteristics of the pier under the action of high speed water flow are summarized. [Results] The monitoring data show that the pier vibration is larger in general when the two gates are opened at the same time, but when the right gate is opened alone, the maximum horizontal vibration peak value is 244. 37 μm and the standard deviation of the maximum displacement level is 60. 89 μm. The maximum ripple pressure root mean square value is 1. 84×9. 8 kPa. [Conclusion] Under the action of high speed water flow, the vibration of gate pier will increase with the increase of gate opening. In the same horizontal direction, the vibration of gate pier will increase gradually along the direction of downstream flow. In the same vertical direction, the vibration effect is more obvious when the pier is closer to the top. The main reason is that the gate is gradually opened, the flow velocity increases, the flow pattern is disturbed, and the pulsating pressure is easy to form, resulting in flow-induced vibration problems,and the end of the pier is less constrained and the vibration is the largest. At the same time, the vibration of the pier is not only affected by the discharge volume of the sluice gate, but also related to the downstream water level, water flow pattern, and the single and porous operation mode of the sluice gate.

[Objective] In order to examine the crucial role of water pollution control in promoting green agricultural development,given its primary status as a water environmental pollutant, by exploring the relationship between water pollution control and agricultural eco-efficiency under economic thresholds, the optimize green agricultural development strategies were seeked.[Methods] Using a three-stage SBM model, the agricultural eco-efficiency was caloulated, which was eliminated the influences of external environments and random errors. A threshold effect model then assesses the differential association between water pollution control and eco-efficiency, identifying specific economic thresholds. [Results] Result reveal a nonlinear relationship characterized by a dual-threshold effect, with thresholds at 8 796 yuan and 12 897 yuan, respectively, across rural economic levels. [Conclusion] It is concluded that external factors like rural economic prosperity significantly affect eco-efficiency estimates, and greater economic affluence leads to a more harmonious relationship between water pollution control and ecoefficiency. Consequently, regions should adjust green agricultural strategies′ priorities based on their rural economic stages to ensure the effectiveness and targeted application of water pollution control measures.

[Objective] To achieve high-precision deformation prediction of crushed stone soil landslides, [Methods] based on the result of landslide exploration and deformation monitoring, multi-scale variable identification of deformation data is first achieved using complementary set empirical modes. Then, a deformation prediction model is constructed using Grey Wolf optimization algorithm, correlation vector machine, and chaos theory to grasp the deformation characteristics of landslides and guide their disaster prevention and control. [Results] The result show that the optimization of the complementary set empirical mode in the construction process can reasonably improve the recognition effect and effectively identify multi-scale variables of landslide deformation data. The combination optimization steps of the prediction process can effectively improve the prediction accuracy,and in the final prediction result of the four monitoring points, the average relative error ranges from 1. 96% to 2. 20%, and the variance value ranges from 0. 002 0 to 0. 003 5, fully demonstrating the strong robustness of the prediction model. [Conclusion] The result indicate that the prediction model considering multi-scale variable identification of deformation data is suitable for predicting the deformation of gravel soil landslides. According to the comparison of its extrapolation prediction result, the existing deformation rate of C1 monitoring point is relatively higher, and the prediction rate of the other three monitoring points is relatively higher. It indicates that the stability of the landslide's trailing edge will tend to be stable, but the stability of its leading edge position will tend to be unfavorable. It is recommended to carry out prevention and control measures for this landslide as soon as possible.

[Objective] The periodic fluctuation of reservoir water level will lead to the strength deterioration and deformation exacerbation of the rock and soil on the reservoir bank slope, which affect the stability of the reservoir bank slope. [Methods] The uniaxial compression tests and CT scanning techniques were employed to study the evolution law of elastic modulus(E),Poisson's ratio(v), and microstructural parameters of strongly weathered granite after multiple cycles of soaking-non soaking in Jiangxi Yanshan Pumped Storage Power Station. The correlation between deformation parameters and microstructure parameters of strongly weathered granite was obtained. Observing The microstructural changes of strongly weathered granite were observed after multiple soaking-non soaking cycles using a polarizing microscope, the structural change characteristics of strongly weathered granite were obtained, and its evolution mechanism was explored by combining the evolution laws of deformation parameters and microstructural parameters. [Results] The result showed that after the 8th soaking-non soaking cycle, the elastic modulus of strongly weathered granite decreased by 50. 34%, and the Poisson's ratio increased by 41. 85%; The projected porosity of the three cross-sections increased by 20. 34%, 19. 18%, and 16. 29% respectively, and the number of pores increased by 52. 99%,42. 24%, and 30. 59% respectively. [Conclusion] The research result indicate that:( 1) The elastic modulus of strongly weathered granite gradually decreases and the Poisson' s ratio gradually increases with the increase of soaking-non soaking cycles. The deformation parameters deteriorate significantly during the first 8 cycles of soaking-non soaking, and deteriorate slowly after 8 cycles.(2) The projected porosity and void number increase gradually with the increase of soaking non soaking cycles, while the average porosity and void area and porosity and void distribution dimension decrease gradually. After 8 cycles of soaking-non soaking, the amplitude of changes in microstructural parameters significantly decreased.(3) Multiple soaking-non soaking cycles caused the development and expansion of internal pores and cracks in strongly weathered granite, resulting in an increase in the number of pores and cracks. Changes in the microstructure of the rock interior lead to deterioration of deformation parameters, reducing the rock's ability to resist deformation.

[Objective] The mechanical strength of the fractured rock body will be deteriorated under loading, which is easy to further trigger rock rupture and affect the rock engineering, and analyze the acoustic emission energy characteristics, the main frequency change and the RA-AF value distribution of the defective sandstone under uniaxial compression. [Methods] Based on the acoustic emission parameters, we investigate the fracture mechanism, crack type and evolution of sandstone, and combined with scanning electron microscopy, we investigate the connection between the fracture micro-morphological characteristics and the macro-fracture. [Results] The presence of defects has obvious deterioration effect on the mechanical strength of sandstone, the change of acoustic emission energy exists in four phases, namely, “fluctuation period, smooth period, violent fluctuation period,and upward surge period”, and the acoustic emission parameter AF mainly distributes in the range of 0~500 kHz, and RA mainly distributes in the range of 0~ 2. 0 ms·V^-1, and the fracture surface of sandstone is divided into three types: tensile fracture,shear fracture, and composite fracture of tension-shear type. The sandstone fracture is divided into three types: tensile fracture,shear fracture, and tensile-shear composite fracture. [Conclusion] (1) The strength of sandstone shows an overall increasing trend with the increase of fracture angle;(2) The crack evolution process can be divided into: initial wing tension crackcomposite type crack(0°~45°) → initial anti-wing tension crack-anti-wing crack(60°~75°) → initial wing tension cracksecondary wing crack(90°);(3) The main frequency signal accounts for 71%~96% of the low-frequency, and the highfrequency accounts for 3%~23%, and the damage process mainly produces large-scale cracks;(4) the proportion of tension cracks is more than 70%, the proportion of shear cracks fluctuates around 20%, and the tension damage is dominant;(5) the fracture of the rupture surface of the sandstone is dominated by transgranular fracture(TG) and accompanied by along-granular fracture( IG), and the intact sandstone is mainly transgranular tensile-type fracture, and defective sandstone is mainly transgranular tension-shear composite-type fracture The macroscopic crack fracture forms of sandstones and the microscopic morphologic features have a corresponding relationship.

[Objective] In the long-term historical geological activities, there are a large number of fractures in the underground rock mass, which is bound to deteriorate the creep mechanical properties of the rock mass and its ability to resist failure. In order to reveal the influence of the change of fracture angle and thickness on the creep mechanical properties and damage damage of rock mass with cross-fractures under the long-term action of graded cyclic loading and unloading. [Methods] According to the cyclic loading and unloading creep test curves, the energy of each stage of cycling was calculated, and the creep mechanical properties and damage laws of different fractured samples were analyzed by energy dissipation method and acoustic emission technology combined with the strength of the sample. [Results] The results showed that the stress-strain curve of the specimen had an obvious hysteresis circle under graded cyclic loading and unloading, and the angle and thickness of the fracture had a deteriorating effect on both the peak strength and the long-term strength, and the influence of the latter was slightly higher than that of the former. The input energy, elastic energy and dissipation energy of the specimen under different fracture conditions are similar, and the damage variable D value increases with the increase of fracture angle and thickness. The cumulative ringing number of AE will have obvious abrupt changes in the process of loading and unloading, and the abrupt range will be larger when cracks occur in the specimen.[Conclusion] The result show that the irreversible damage caused during the test is the main factor leading to the change of specimen strength from the hysteresis loop and energy damage D value. The larger the crack thickness and angle of the specimen, the earlier the signal appears and increases, and the less stress occurs when the specimen is damaged.

[Objective] Focusing on loess from the Xining region of Qinghai, the mechanical properties and micro-mechanisms of lignin-modified loess under freeze-thaw cycles are investigated. [Methods] Freeze-thaw cycle tests are conducted on ligninmodified soil under closed system conditions. Basic physical property tests, unconfined compressive strength tests, and thermal tests are performed to comprehensively evaluate the reinforcement effects of calcium lignosulfonate(CL), sodium lignosulfonate(SL), and unsulfonated lignin(SFL) on loess. Scanning electron microscopy and X-ray diffraction are used to analyze the soil structure and composition. [Results] With the increase in freeze-thaw cycles, the strength of the soils at the same dosage decreases in the following order: CL-modified soil > SFL-modified soil > SL-modified soil. The thermal conductivity decreases in the order of SFL-modified soil > CL-modified soil > SL-modified soil. SFL-modified soil exhibits the lowest pH value and the best conductivity. [Conclusion] The result indicate that the addition of lignin effectively enhances the strength and thermal insulation capacity of loess while reducing its pH value. SFL-modified soil demonstrates significant advantages, as the C = O double bonds present in SFL contribute to lower pH values and higher conductivity in the stabilized soil. The thermal insulation performance benefits from the high quartz content. Under freeze-thaw cycles, both CL and SFL-modified soils enhance frost resistance and structural stability by promoting the formation of calcium and magnesium cementation between soil particles, thereby mitigating the negative impacts of frost heave on the mechanical properties of the soil. Furthermore, considering the significant performance improvements and economic benefits of SFL, it is prioritized as the material for loess improvement in frozen soil regions. The research findings provide a theoretical basis and scientific reference for loess improvement efforts in Northwest China.

[Objective] To accurately predict the compressive strength of concrete, highlight the predictive advantages of the XGBoost model, and realize the interpretable function of the XGBoost model, [Methods] a data set of 1030 samples with eight factors such as cement, age, water and others as input features and compressive strength as target features is constructed, and machine learning algorithm models of Support Vector Regression(SVR), Random Forest(RF) and Extreme Gradient Boosting Tree(XGBoost) to research on concrete compressive strength prediction, comparing the prediction result of the XGBoost model and the ACI209 formula, and meanwhile, introducing the SHAP model to explain and analyze the XGBoost model. [Results] The result show that the XGBoost model has the highest prediction accuracy with R² of 0. 952, MAE of 2. 48, MAPE of 9. 16, and RMSE of 3. 58; however, the prediction error of the XGBoost model for low compressive strength samples less than 30 MPa is larger, and the prediction accuracy of the XGBoost model improves as the compressive strength increases, and the proportion of exceeding the limit samples decreases from 25% to 2. 7%; compared with the prediction result of ACI209 formula, the mean absolute error rate of the XGBoost model's prediction values for samples of age 56 d and 100 d are 4. 10% and 3. 64%, compared with 11. 27% and 17. 96% for ACI209 formula. [Conclusion] The XGBoost model is suitable for the prediction of samples with concrete strength greater than 30 MPa; The SHAP model can not only quantitatively give the ranking of feature importance, but also qualitatively give the influence of each feature parameter on compressive strength, which can provide a reference for concreterelated research and other studies that need to explain machine learning models.