[Objective] With global warming, compound extreme climate events pose more significant adverse impacts on human development and ecological environments than single extreme climate events. [Methods] Based on daily average temperature and precipitation data from 29 meteorological stations in the Minjiang River Basin from 1980 to 2021, the percentile method(90th and 10th percentiles) was used to identify compound extreme climate events. The frequency, trend, and intensity of four types of compound extreme climate events(Warm-Dry, Warm-Wet, Cold-Dry, and Cold-Wet) in the Minjiang River Basin were analyzed. [Results] The result indicate that: 1) Warm-Dry events dominate the compound extreme events in the Minjiang River Basin, with the highest annual average frequency of 76.15 days. Cold-Dry events follow, with an annual average frequency of 53.32 days. On a seasonal scale, Warm-Dry events have the highest frequency, each exceeding 15 days. Cold-Dry events are most frequent in autumn and winter, each also exceeding 15 days. The frequencies of Warm-Wet and Cold-Wet events are relatively low. 2) Spatially, high-frequency areas of Warm-Wet and Warm-Dry events are located in the southern Jianxi Basin, eastern Futunxi and Shaxi Basins, and the eastern and northern middle-lower reaches of the Minjiang River Basin. Cold-Wet and Cold-Dry events mainly occur in the northern Jianxi Basin, western Futunxi and Shaxi Basins, and the southwestern middle-lower reaches of the Minjiang River Basin. 3) Warm-Dry events show a significant increasing trend, while Cold-Dry events exhibit a significant decreasing trend. Among sub-basins, the Shaxi Basin shows the most significant increasing trend for Warm-Dry events, at 13.58 days per decade, while the Futunxi Basin shows the most significant decreasing trend for Cold-Dry events, at-7.49 days per decade. 4) In terms of intensity, although Warm-Wet events have a lower frequency, they exhibit higher intensity, predominantly at strong and moderate levels, with more moderate-level days than strong-level days. Warm-Dry events also predominantly occur at strong and moderate levels, with more strong-level days than moderate-level days. [Conclusion] Overall, Warm-Dry events are the most prevalent in the Minjiang River Basin, with high intensity and an increasing trend. Cold-Dry events mainly occur in autumn and winter, with a decreasing trend. Under extreme precipitation impacts, Warm-Wet events exhibit high intensity but low frequency.

[Objective] The Meiyu phenomenon stands as a distinctive weather occurrence in East Asia, with its precipitation levels during this period exerting significant influence on the emergence of droughts and floods during the summer, thereby incurring substantial socio-economic losses. Therefore, it is necessary to analyze the precipitation characteristics and influencing factors during the Meiyu period over the Yangtze-Huai River Basin, which will help to provide reference for the early warning of drought and flooding. [Methods] This study used observed daily precipitation data from 239 meteorological stations over the Yangtze-Huai River Basin from 1961 to 2020 combined with NOAA and ERA5 reanalysis data to analyze the frequency of the number of days without rainfall and heavy downpour and through the application of Empirical Orthogonal Functions(EOF), it examines the precipitation patterns during the Meiyu period, alongside its correlation with sea surface temperature(SST) and water vapor flux. [Results] Over the Yangtze-Huai River Basin, the average number of days without rainfall during the Meiyu period is distributed incrementally from south to north, and there is a significant increasing trend in Jianghuai area(area Ⅲ) from 1961 to 2020. Over the past six decades, the basin has witnessed 47 heavy downpour events, and the number of stations with daily precipitation up to the level of exceptionally heavy rainfall on each date during the Meiyu period had a significant upward trend. Two primary spatial precipitation distribution patterns emerge during the Meiyu period within the basin: one demonstrating uniform basin-wide trends, showcasing an overall upward trend in precipitation, while the other manifests a north-south antiphase distribution. [Conclusion] The increase in the number of days without rain and the number of stations with precipitation up to the level of exceptionally heavy rainfall during the Meiyu period over the Yangtze-Huai River Basin need to be of some concern. A notable correlation between the Nino3.4 index and Meiyu period precipitation, with higher(lower) Nino3.4 values indicative of increased(decreased) Meiyu precipitation in the Yangtze-Huai River Basin. Furthermore, precipitation fluctuations during this period exhibit significant positive correlations with SST anomalies across tropical Indian Ocean, tropical central-eastern Pacific, and tropical Atlantic regions during preceding winter, spring and concurrent periods. Specifically, positive SST anomalies in these regions correspond to increased Meiyu precipitation, and vice versa. Water vapor transport influencing Meiyu period precipitation primarily originates from the Bay of Bengal, South China Sea, and the western periphery of the western Pacific subtropical high. By June, the convergence of water vapor transport from the South China Sea and western Pacific fosters a robust water vapor flux belt. Subsequently, in July, intensified water vapor transport from the South China Sea and Bay of Bengal further fortifies this flux belt.

[Objective] With the acceleration of urbanization and the frequent occurrence of extreme weather events, urban flooding events are becoming more and more severe, and the risk of vehicle instability in waterlogged road sections is gradually increasing. The study of vehicle instability risk thresholds in waterlogged roads is of great theoretical significance and practical value for flood risk assessment and emergency management. [Methods] The research result on vehicle instability thresholds in flooded water from 1967 to 2024 are systematically summarized from experimental studies, theoretical analyses, and numerical simulations, and the advantages and disadvantages of basing on a single water depth/flow velocity, a combination of water depth and flow velocity, vehicle characteristics, and hydrodynamics as the existing vehicle instability discriminatory criteria are evaluated. [Results] Existing flume tests consider more limited influencing factors, less research on foot-scale tests and non-static vehicles, some theoretical analyses lack rate verification of data, and some hydrodynamic models in numerical simulations do not carry out parameter sensitivity analyses. The threshold value does not fully consider the vehicle conditions, driving conditions, road environment and other factors. The destabilization criterion mainly relies on vehicle dynamics parameters, which is somewhat empirical. [Conclusion] In the future, it is necessary to carry out multi-factor coupling research on different types of foot-size vehicles, and combined with numerical simulation, use machine learning algorithms to analyze the experimental datum, to improve the accuracy of the vehicle stability threshold model under flooding conditions, and to formulate vehicle safety standards. To provide a decision-making basis for the transportation department and the drainage system planning and construction departments.

[Objective] Investigating extreme rainfall patterns in the context of global climate change can aid in ecological protection, climate change response, water resource management, and environmental impact assessment. [Methods] Utilizing daily precipitation data from 27 meteorological stations in Shanxi Province from 1975 to 2020, extreme precipitation events over a span of 46 years were selected. Ten extreme precipitation indices recommended by ETCCDMI were calculated. Eleven characteristic indicators, including significance level(P_value), trend Slope(Slope), Mean value(Mean_value), and Median value(Median_value), were used to analyze the trends and distribution of the data. The corresponding extreme precipitation index characteristics were calculated by superimposing landform types, analyzing the intensity, distribution, and trend changes of extreme rainfall events across different landform types, exploring the correlation between extreme rainfall and landform types, and revealing the distribution characteristics of extreme rainfall in various landform types. [Results] All sites in Shanxi Province showed a decreasing trend in CDD, with 81% of the sites reaching significance. Except for CWD, the other eight extreme precipitation indices had more sites with positive correlations, with the proportions of sites positively correlated with PRCPTOT, R10mm, Rx1day, and Rx5day reaching 74%, 74%, 69%, and 67%, respectively, although the overall significance was low. The spatial distribution of CDD in Shanxi Province exhibited an increasing trend of reduction from south to north and west to east. Six indices, including the Mean value of CDD, showed similar spatial distribution characteristics, gradually decreasing in a gradient from north to south. Three indices, including CV, shared similar spatial distribution characteristics, with a radiating decrease from north to south at the junction of Yangquan and Xinzhou in the southeast. The drought situation in the northern part of Shanxi Province alleviated faster than in the southern part. There was a significant correlation between elevation in Shanxi Province and the indices CDD, CWD, PRCPTOT, R10mm, and Rx5day. CDDSlope, the Median of CWD, Ave_Year_Change, Q50 value, and the Minimum value of Rx5day all showed significant negative correlations(-0.44,-0.41,-0.42,-0.41,-0.45), while the Slope values of PRCPTOT and R10mm showed significant positive correlations(0.46, 0.45). All six indicators of SDII showed significant negative correlations, indicating a significant overall impact on SDII. [Conclusion] The relief amplitude of Shanxi Province had no significant correlation with the characteristic values of extreme climate indices. The distribution characteristics of extreme precipitation index characteristic indicators varied across different landform types in Shanxi Province. Indicators were more scattered in low-altitude hilly terraces, small undulating middle mountains, and mid-altitude hilly terraces, requiring consideration of spatial variation within these landform types regarding extreme climate indices.

[Objective] In order to investigate the role of sponge cities in mitigating urban waterlogging by selecting the Jincun development area of Jincheng City as a research area and analyzing the regulation effects of low impact development(LID) facilities on runoff and waterlogging at different spatial scales. [Methods] A coupled urban stormwater and waterlogging model was developed by integrating the Storm Water Management Model(SWMM) and the two-dimensional module of InfoWorks ICM. The model simulated various storm scenarios and LID layout schemes to analyze rainfall-runoff processes and waterlogging characteristics in plots, drainage zones, and regions. [Results] The findings indicated that LID facilities effectively reduced runoff peak values, decreased total runoff, accelerated runoff recession, and mitigated overflow nodes and overloaded pipe segments. They also significantly reduced areas affected by waterlogging and lowered water depths. The regulation effect of LID facilities showed minor variation across different spatial scales and performed well within a 1 to 5-year recurrence period. Specifically, under 1-year recurrence period rainfall, the largest LID layout scheme reduced surface runoff by more than 75%. [Conclusion] LID facilities demonstrate strong efficacy for short-recurrence-period storms but have limited capacity for long-recurrence-period waterlogging control, particularly at severe waterlogging points. Expanding the scale of LID facilities can substantially enhance their runoff regulation capacity.

[Objective] This study aims to investigate the role of sponge cities in mitigating urban waterlogging by selecting the Jincun development area of Jincheng City as a research area and analyzing the regulation effects of low impact development(LID) facilities on runoff and waterlogging at different spatial scales. [Methods] A coupled urban stormwater and waterlogging model was developed by integrating the Storm Water Management Model(SWMM) and the two-dimensional module of InfoWorks ICM. The model simulated various storm scenarios and LID layout schemes to analyze rainfall-runoff processes and waterlogging characteristics in plots, drainage zones, and regions. [Results] The findings indicated that LID facilities effectively reduced runoff peak values, decreased total runoff, accelerated runoff recession, and mitigated overflow nodes and overloaded pipe segments. They also significantly reduced areas affected by waterlogging and lowered water depths. The regulation effect of LID facilities showed minor variation across different spatial scales and performed well within a 1 to 5-year recurrence period. Specifically, under 1-year recurrence period rainfall, the largest LID layout scheme reduced surface runoff by more than 75%. [Conclusion] LID facilities demonstrate strong efficacy for short-recurrence-period storms but have limited capacity for long-recurrence-period waterlogging control, particularly at severe waterlogging points. Expanding the scale of LID facilities can substantially enhance their runoff regulation capacity.

[Objective] With the goal of mitigating or inhibiting the severity of urban storm waterlogging, the inhibitory effect of soil permeability changes on urban storm waterlogging is studied. [Methods] Hydrological and hydrodynamic methods, infiltration coefficient calculation, and scenario setting were used to comprehensively construct the urban rainstorm waterlogging numerical model and infiltration volume model. The effects of different levels of vegetation coverage on factors such as depth, area, volume, and duration of waterlogging on the urban subsurface were investigated. [Results] The results showed that: in terms of waterlogging water depth, in Scenario 1, the maximum and minimum water depths were 1.30 m and 0.10 m, respectively. In Scenario 2, the maximum and minimum water depths were 0.95 m and 0.05 m, respectively. In Scenario 3, the maximum and minimum water depths were 0.35 m and 0.01 m, respectively. As for waterlogged area, the areas in Scenario 1, Scenario 2, and Scenario 3 were 28.96 km², 14.40 km², and 4.16 km², respectively. In terms of water volume, the reduction rate of water volume in the study area decreased as the rainfall intensity increased, and the difference decreased with the increase in rainfall intensity. In terms of water level in the study area, the maximum water level decreased due to the increase of vegetation coverage, with the reduction rate fluctuating between 5% and 20%, but the overall change was minor. In terms of waterlogging delay time in the study area, the time difference for the maximum average water level in Scenario 1 and Scenario 3 were 60 minutes. [Conclusion] Increasing urban vegetation coverage can effectively mitigate the severity of urban storm waterlogging. The results of this study not only serve as a reference for the rational planning of urban green spaces, but also provide a decision-making basis for the government emergency departments in their disaster response efforts.

[Objective] In view of the various uncertainties of grid-connected power systems with a high proportion of renewable energy, in order to maintain the stability and economy of the system, a probabilistic transient stability constrained optimal power flow(PTSCOPF) method considering multiple uncertainties is proposed. [Methods] Firstly, taking into account the uncertain factors, probabilistic models of uncertainty variables of wind power output, load, fault type, fault location and fault clearance time are established. Secondly, the PTSCOPF model based on chance constraint optimization theory is constructed. Then, combined with the multipoint estimation method based on Gauss-Hermite integral and the Gram-Charlier series, the random variables are treated deterministically. Then particle swarm optimization(PSO) algorithm and ant colony optimization(ACO) algorithm are combined to realize the effective solution of PTSCOPF model. Finally, simulations are conducted on the modified IEEE 39-bus test system. [Results] The relative error and mean of the standard deviation of the output random variables computed using the multi-point estimation method based on Gauss-Hermite integration are less than 2.0%, and the method in this paper achieves the optimization of the way the system operates with a computation time of 27.9 s and an expected cost of 62 610 $·h^-1, and the value of the transient stability index of the system is 62.4 after the optimization. [Conclusion] The results show that after the occurrence of the fault, under the condition of considering multiple uncertain factors, the proposed method in this paper can realize the reliable improvement of the transient stability of the system with low computational time cost while taking into account the economy of the system, so that the system can transition to the transient stable state, which guarantees the safe and stable operation of the power system.

The offshore wind turbine foundation is composed of massive reinforced concrete. Apart from its crack-limiting effect, steel reinforcement can also enhance the load-bearing capacity of the concrete structure and influence the development and distribution of the temperature field. The role of steel reinforcement cannot be neglected in the simulation analysis of the temperature and stress fields of the foundation. While the precise algorithm for simulating every steel reinforcement bar is computationally intensive, the average equivalent algorithm based on reinforcement ratio neglects the interaction between steel reinforcement and concrete. Therefore, an equivalent calculation method for thermal and mechanical parameters of massive reinforced concrete is proposed, aiming to reflect the macroscopic role of steel reinforcement while considering its local effects. Then the accuracy of these method in predicting the temperature and stress field changes of reinforced concrete were verified by using simplified models. Taking the Leting offshore wind turbine foundation as a case study, this paper compares the Equivalent Reinforced Concrete(ERC) model with the Plain Pile-cap Concrete(PPC) model to analyze the effect of reinforcement on temperature and stress changes in foundation concrete. Simulation result reveal that reinforcement can lower the maximum temperature of the foundation concrete, with a reduction of about 1.2℃ at the center of the foundation and more than 8℃ in areas with dense reinforcement, while also decreasing the internal-external temperature difference. The surface concrete of the foundation experiences tensile stress during the early stages of heating, and the internal concrete of the foundation develops tensile stress during the later stages of cooling. Under the influence of reinforcement, the former was reduced by 0.34 MPa, a reduction rate of 22.37%, and the latter was reduced by 0.87 MPa, a reduction rate of 24.79%. Acting as a low thermal resistance pathway, the reinforcement′s high thermal conductivity effectively lowers the maximum temperature and the internal-external temperature difference in the foundation concrete, reducing the stress induced by temperature. Additionally, the difference in the coefficient of thermal expansion between steel and concrete result in compressive stress in the surrounding concrete during the later stages of cooling, further decreasing the maximum tensile stress in the internal concrete areas of the foundation, thereby reducing the risk of cracking in the foundation concrete.

[Objective] Deformation is a direct characterization of the overall serviceability of dams under the coupling of reservoir water, temperature and material properties, etc. The establishment of an accurate and efficient prediction model is of great significance in grasping the deformation trend of dams and assessing the risk of dams. [Methods] Aiming at the problems of low accuracy, poor adaptability and weak noise immunity of traditional prediction models, a deep learning prediction model for concrete arch dam deformation is proposed by combining the Harris Hawk algorithm(HHO), Variational Modal Decomposition(VMD), Random Forest algorithm(RF), and Long-Short-Term Memory neural network(LSTM). First, the HHO algorithm is improved by introducing Tent chaotic mapping, energy randomness decreasing strategy, and the arch dam deformation data sequence is decomposed to obtain a number of modal components(IMF) with different frequencies using the IHHO-VMD method. Secondly, The RF algorithm is utilized to calculate the contribution of deformed characteristic factor and to screen the optimal set of input factors for the prediction model;. Finally, the LSTM model is used to learn and predict each IMF component, and the final deformation prediction is obtained by reconstructing the predicted values of each component. [Results] The simulated signal decomposition result show that compared with the existing signal decomposition method, the optimal signal decomposition can be realized by using the IHHO-VMD method. Analyzed by a project example, the proposed model predicts the displacement of four measurement points with average RMSE, MAE, R² and MAPE of 0.397 6 mm, 0.327 5 mm, 0.991 8 and 1.519 4%. [Conclusion] Compared with other combined models, the result of the four evaluation indexes of the proposed model are optimal, indicating that the model has the advantages of high prediction accuracy, good generalization ability and robustness.

[Objective] Tunnel projects in high-altitude cold areas are increasing year by year under the national development environment. Tunnel opening frost damage is widespread, and at this stage, the frost protection technology is mainly passive thermal insulation and frost protection technology. [Methods] Based on this, a numerical model of electric heating active protection for high-altitude cold tunnels is established. The tensile damage of the lining under different ambient temperatures, the inhibition effect of electric heating technology on the freezing of the surrounding rock, and the low-temperature deterioration of the lining are analyzed. And the influence of different electric heating power, burial depth, working time, and thickness of insulation board on the protection effect are explored. [Results] The result of the study show that:(1) The damage of tunnel lining becomes more and more serious with the decrease of temperature. Composite electric heating technology can effectively solve the problem of low-temperature damage deterioration;(2) With the lowering of the ambient temperature, the thermal power of the electric heating system of the alpine tunnel increases;(3) Electric heating tape should be laid on the surface of the alpine tunnel lining, and supporting the use of a thickness of about 5 cm of the thermal insulation layer is more effective;(4) The tunnel lining temperature with the change in the ambient temperature with hysteresis. It is recommended to switch on the electric heating system about 15 days before the start of the cold season, and switch off the system 7 days in advance. [Conclusion] Electric heating technology in tunnel insulation and frost protection can greatly improve the effect of insulation and frost protection. Different ambient temperatures require different power of the electric heating system. Through the parametric analysis of electric heating, reasonable construction recommendations are made to guide the application of electric heating technology in tunnel engineering.

[Objective] With the implementation of the strategy of large-scale development of the western region, the problem of reducing the mechanical properties of the foundation caused by karst geology has gradually emerged, which has had a non-negligible impact on the construction of the project and the safety of the people. At the same time, complex karst caves are often difficult to be accurately detected due to their concealment, which further increases the risk of engineering construction. Therefore, a combination of qualitative and quantitative analysis was established to accurately detect and characterize karst caves. [Methods] Taking the karst cave detection in a residential building construction project in Zunyi City as an example, firstly, the high-density electric method is used to detect the field area, and the data of the direction and development range of the karst cave are obtained. Secondly, 3D laser scanning technology was used to obtain detailed data of karst cave morphology and three-dimensional spatial distribution. Finally, the high-density electrical detection result and the 3D laser scanning result were compared and analyzed. [Results] The result show that the cave strikes NNW-SSE from the high-density electrical inversion result, and the 3D laser modeling shows that the buried depth of the cave gradually increases from north to south, and the total volume of the cave is 2 795.48 m³, the height is between 0.5~8.57 m, and the width is between 1.97~23.34 m. The combination analysis of the two method shows that the plane position deviation of the karst cave is between 0~18 m, the deviation rate is 0%~112.5%, and the depth deviation is between 2~8 m, and the deviation rate is 8%~33.3%. [Conclusion] The result show that the high-density electrical method combined with 3D laser scanning can be used to detect karst caves, from qualitative analysis to quantitative description, the information of the buried depth, height change and development scale of karst caves, as well as the deviation rate obtained by comparative analysis, which can identify karst caves that cannot be entered by humans, and realize the fine detection of complex karst caves. It can be seen that the combination of high-density electrical method and 3D laser scanning method is an effective combination of technical method for fine detection of karst caves.

[Objective] This study aims to clarify the structure of non-point source pollution in the watershed and conduct a detailed analysis of the spatial and temporal characteristics of non-point source pollution loads. [Methods] The SWAT(Soil and Water Assessment Tool) watershed non-point source pollution model was used as a basis., Representative hydrological series wereas selected, and combined with an inflow pollution load calculation model., A technical process was developed to identify key non-point source pollution areas based on pollution load and inflowintensity. This process was verified in the Shahe Reservoir watershed, where data conditions were relatively complete. [Results] The results showed that the total inflow load of total nitrogen(TN) in the Shahe Reservoir watershed was found to be 198.34 t/a, with non-point source pollution accounting for 86.53% of this load. The largest contribution to the TN load came from tea gardens in the watershed, contributing 23.84%. The TN load during wet years and extremely wet years increased by 58.06% and 289.09%, respectively, compared to dry years., During the wet season, the average monthly TN load was 75.24% and 372.51% higher than in the normal and dry seasons, respectively. The river reduced the TN load by 33.58 t/a, with a reduction ratio of 14.48%. The variation in TN inflow pollution intensity across sub-watersheds ranged from 0.36 t/km² to 4.73 t/km². The low-value zones for non-point source pollution emissions were primarily located in the southern part of the watershed, while the high-value zones were concentrated near the reservoir. The incflow TN intensity per unit area in the Shahe West and Shahe East control sub-zones was significantly higher than in the southern part of the watershed. [Conclusion] Pollution control efforts should be strengthened in areas with high pollution yieldss, high pollution regions, and during high pollution periods. The established technical process can effectively identify and scientifically analyze key non-point source pollution areas in the watershed, providing technical support for non-point source pollution prevention and ecological adaptive development in watershed water environments. This will ensure more targeted and effective pollution control measures.

[Objective] The construction of weirs changes the hydraulic characteristics of rivers and affects the structure of phytoplankton communities and the health of aquatic ecosystems in the river. This study aims to explore the nonlinear response relationship between phytoplankton community structure and its driving factors in spring and autumn in Furong Creek under the construction of cascade weirs. [Methods] The structure of phytoplankton communities and related environmental factors were investigated in Furong Creek from 2023 to 2024. This study focused on the analysis of the changes of nutrient concentrations and biomass of phytoplankton in autumn and spring within the same dry season in Furong Creek. Redundancy analysis was used to identify the key factors influencing the structure of phytoplankton communities. The MIKE 11 model was employed to simulate the hydrodynamic changes in the river. Combined with total nitrogen and permanganate index, a GAM model of phytoplankton diversity index and hydrodynamic factors was developed, and the change of phytoplankton diversity after the optimized layout of the cascade weirs was fitted. [Results] The result showed that the annual average value of Shannon-Wiener diversity index of phytoplankton in Furong Creek was 2. 79, which was in a state of mild pollution. A total of 239 species from 95 genera in 8 phyla were identified. Among the phytoplankton, Chlorophyta was the dominant group throughout the year in Furong Creek, followed by Bacillariophyta and Cyanophyta. The cell abundance of phytoplankton ranged from 3. 11 to 20. 64 mg/L and from 0. 23 to 6. 31 mg/L in spring and autumn, which indicated a clear seasonal succession of phytoplankton community structure. Compared with autumn, the relative abundance of Cyanophyta significantly decreased in spring across the whole river section, while Chrysophyta and Dinophyta showed significant increase at some monitoring sites, leading to water bloom phenomenon and a noticeable decline in the diversity of phytoplankton. The dominant species in the water bodies throughout the year were Cyclotella catenata, Chlorella vulgaris, Scenedesmus bijuga, Scenedesmus quadricauda, Chroomonas acuta, Cryptomonas ovata, and Cryptomonas erosa. Redundancy analysis(RDA) showed that hydrodynamic factors(v, h) and water environmental factors(TN, COD_Mn) were the main influencing factors of phytoplankton community structure. [Conclusion] The result show that the nutrient concentration, phytoplankton biomass, and density in Furong Creek in spring are significantly higher than in autumn. The GAM model, constructed by combining hydrodynamic and environmental factors, can effectively reflect the nonlinear relationship between phytoplankton diversity index and its driving factors. In spring, with an increase in nutrient concentration, the habitat conditions of low flow speed and high water depths formed by overflow weirs will lead to a decrease in the Shannon-Wiener index of phytoplankton and an intensified risk of eutrophication. However, a reasonable layout scheme of cascade weirs will improve the diversity of phytoplankton and reduce the risk of eutrophication in the river. The findings of this study can help deepen the understanding of the ecological and environmental effects of cascade weir construction in the river.

[Objective] This study aims to reveal the intrinsic relationship between land use and land cover(LULC) in ecological function zones and ecosystem service value(ESV), which is crucial for effectively maximizing ecosystem benefits and advancing regional ecological civilization. [Methods] The ESV of the Tumen River Basin was assessed using modified standard equivalent factors. Geodetector was used to analyze the relationships between ESV and potential influencing factors, including temperature(TEM), precipitation(PRE), normalized difference vegetation index(NDVI), elevation(DEM), soil organic matter content(SOMC), and human activity intensity on land surfaces(HAILS), as well as their influence on the spatiotemporal evolution of ESV. Furthermore, based on the Territorial Spatial Plan of Jilin Province(2021—2035) and the Overall Territorial Spatial Plan of Yanbian Korean Autonomous Prefecture(2021—2035), the PLUS model was used for spatially constrained multi-scenario settings to explore the spatial changes of ESV in the Tumen River Basin under the natural development scenario(S1) and the target-oriented scenario(S2) in 2030. [Results] The result indicated that from 2000 to 2020, the total ESV of the study area fluctuated but showed an overall upward trend, with the largest increase observed between 2005 and 2010, where the ESV increased by 0.87×10¹⁰ yuan within five years. Forestland contributed the highest ESV, accounting for nearly 94% of the total value. Regulating service value(RSV) and supporting service value(SSV) were the dominant ecosystem services. Geodetector result showed that HAILS(q=0.678) was the primary factor influencing the spatial variation of ESV, followed by TEM(q=0.470) and NDVI(q=0.435), while DEM and SOMC had relatively minor impacts. Correlation analysis revealed that ESV was negatively correlated with the landscape shape index(SI)(-0.65) but positively correlated with the Shannon diversity index(SHDI)(0.72) and aggregation index(AI)(0.60). The PLUS simulation result indicated that, by 2030, forestland would still have the highest ESV. The unit ESV of different land use types in 2030, predicted by the grey model(GM)(1,1) were: cultivated land, 3 394.79 yuan/hm²; grassland, 10 367.71 yuan/hm²; water areas, 107 954.26 yuan/hm²; unused land, 558.64 yuan/hm²; and wetlands, 44 708.07 yuan/hm². [Conclusion] The observed changes in high-value and low-value ESV areas under different scenarios further validate the scientific basis of the Plans and the necessity of their implementation. This study provides spatial visualization analysis and data support for achieving planning goals by predicting the spatial evolution of ESV under different land resource management strategies. Additionally, it serves as a reference for comprehensive land resources and environmental protection planning and the sustainable development of ecological function zones in China's northeastern border area.

[Objective] In order to explore the characteristics of soil and water change and the mechanism of slope deformation and failure under the combined infiltration of rainfall and groundwater. [Methods] Therefore, two model tests of different groundwater infiltration head height and rainfall phase combination were designed with silty clay to monitor soil volume water content and pore water pressure, and to study the response characteristics of soil and water in the slope and the instability mode. [Results] The result show that the seepage field inside the slope changes under the combined infiltration of rainfall and groundwater. When the groundwater infiltration head is low, the soil at the bottom of the slope receives groundwater and rainfall infiltration, and the soil at the foot of the slope and the middle and upper part of the slope receives rainfall infiltration. When the groundwater infiltration head is high, the soil in the bottom, foot and middle of slope receives groundwater infiltration, and the soil in the upper slope receives rainfall infiltration. And the wetting front develops in parallel to the slope top, slope surface and slope bottom. [Conclusion] When the soil in front of the slope is saturated, the slope is dominated by flow slip. However, when the groundwater infiltration head is low, the flow slip range is small and it takes a long time to reach the unstable equilibrium.

[Objective] The deformation of support structures is crucial for the stability of deep excavations. To more accurately predict the deformation of support structures caused by deep excavation, [Methods] this paper proposes a novel deformation prediction model, SSBA, which integrates Spearman correlation coefficient, Spatio-temporal Convolutional Neural Networks(STCNN), Bi-directional Long-Short Term Memory, and Attention mechanism. [Results] Experimental result reveal that the deformation of the pit is positively correlated with excavation depth and phase, and negatively correlated with the support strut axial force. Excavation depth having the most significant impact on deformation. Analysis of the monitoring data revealed that the deformation of the support structure is less than the specified values, indicating that the internal support system effectively restricts the lateral displacement of the wall, and the support structure design is reasonable. Compared with four baseline models, the SSBA model achieved the smallest MAE and RMSE values and the largest R² value, indicating that it can predict the support structure deformation more accurately. The SSBA model can also predict the deformation values at different measuring points accurately, demonstrating good generalization capability and reliability. Through experiments conducted using field monitoring data from a certain foundation pit on Suzhou Metro Line 6, it was found that the SSBA model can more accurately predict diaphragm wall deformations, indicating that the model has good generalizability. [Conclusion] SSBA model can predict the deformation of support structures more accurately and provide guidance for the engineering construction.

[Objective] To study the capillary water absorption characteristics of red mudstone and the change rule of water absorption with time, to put forward the prediction method of water absorption of mudstone, and to carry out the calculation of the critical value of water absorption accordingly, so as to provide references for the prediction of water absorption, theoretical and experimental research on the softening characteristics of water absorption and the analysis of disaster-causing mechanism of red mudstone under the condition of groundwater. [Methods] The red mudstone of the Tertiary Mingshan Formation of Yaan, Sichuan, the Cretaceous Guankou Formation of Jianyang, Sichuan, and the Cretaceous Jishan Formation of Chengxian, Gansu, were taken to carry out the capillary water absorption test, and combined with the X-ray diffraction test, the pressurized mercury test, the contact angle test, and the SEM test, to analyze the micromineral compositions of the red mudstone, the pore structure, the microstructural changes before and after capillary water absorption, the characteristic curves of capillary water absorption law and its influencing factors. [Results] The results show that: the capillary water absorption characteristics of the red bedded mudstone in different regions have some differences, and the capillary water absorption rate is decreasing; the capillary absorption coefficients are positively correlated with the absorption rates; the absorption heights show a good linear relationship with the square root of time; based on the L-W equation and the theory of capillary water absorption in porous media, and considering the influence of mineral composition on the capillary water absorption, a time course model of capillary water absorption is proposed; the capillary water absorption rate is negatively correlated with the content of quartz(R²=0.79) and positively correlated with the content of clay minerals(R²=0.80). [Conclusion] The capillary water absorption characteristics and influencing factors of mudstone have certain regularity, and the capillary water absorption of red bedded mudstone is divided into water adsorption phase and water migration phase at the microscopic level; the proposed time-course model of capillary water absorption can effectively carry out the prediction of the water absorption of red bedded mudstone, and the error is small.

[Objective] The mechanical parameters of bedding planes have a significant influence on the initiation and propagation of hydraulic fractures in shale. However, current research on the effects and mechanisms of bedding plane inclination angle and strength on fractures remains limited. [Methods] ABAQUS finite element software was utilized in this study to conduct two-dimensional numerical simulations by adopting the global zero-thickness cohesive element. Python programming was employed to extract the mechanical parameters of hydraulic fractures, and the effects of bedding plane inclination angle, bedding plane strength, and in-situ stress difference on fracture propagation were analyzed. [Results] The result indicated that:(1) the bedding plane inclination angle had a significant impact on the propagation patterns of hydraulic fractures. Within the range of 0° to 90°, when the bedding plane inclination angle was 45°, the fracture length was the longest, and the number of fractures was the largest.(2) Weaker bedding plane strength result ed in more significant effects of the bedding plane on the propagation path of hydraulic fractures, making it easier for narrow-width shear fractures to develop along the bedding plane.(3) When the difference in stress increased from 2 MPa to 8 MPa, the deflection effect of hydraulic fracturing fractures became more prominent, meaning that the fractures were more likely to propagate in the direction of the major principal stress.(4) Compared with bedding plane strength and in-situ stress difference, the bedding plane inclination angle had a more significant impact on hydraulic fractures.(5) Based on the interaction between hydraulic fractures and bedding plane, fracture patterns were divided into four types: penetration, deflection, bifurcation, and capture. As the bedding plane inclination angle increased, hydraulic fractures transitioned from penetration to bifurcation or deflection. [Conclusion] Among the three influencing factors, namely bedding plane inclination angle, bedding plane strength, and in-situ stress difference, bedding plane inclination angle has the most significant effect on the hydraulic fractures.

[Objective] This study aims to identify the variation patterns of soil erosion under different conditions and provide scientific guidance for the prevention and control of soil erosion. [Methods] The study focused on soil erosion on the slope surfaces in the karst rocky mountain areas of northern Guangxi. Based on indoor artificial rainfall simulation experiments, the effects of different fracture degrees, rainfall intensities, and slopes on runoff and sediment yield were systematically analyzed. The accuracy and validity of the simulation experiment were verified by comparing it with field monitoring data on soil erosion. [Results] The results revealed the following:(1) When the fracture degree remained constant, at a rainfall intensity of 15 mm/h, compared to the soil erosion at a 0° slope, the average increase in soil erosion at 3°, 6°, and 9° slope was 70.13%. At a rainfall intensity of 30 mm/h, compared to the soil erosion at a 0° slope, the average increase in soil erosion at 3°, 6°, and 9° slopes was 42.53%. At a rainfall intensity of 60 mm/h, compared to the soil erosion at a 0° slope, the average increase in soil erosion at 3°, 6°, and 9° slope was 35.07%. As the slope increased, soil erosion increased. However, the rate of increase gradually slowed, with the deceleration becoming more apparent.(2) When the slope and rainfall intensity were constant, the fracture degree had a relatively small effect on soil erosion. As the fracture degree increased, soil erosion generally showed a decreasing trend, but the reduction was modest. When the slope and fracture degree were constant, and rainfall intensity was 15~30 mm/h, higher rainfall intensity resulted in a greater increase in soil erosion. When the rainfall intensity exceeded 30 mm/h, soil erosion continued to increase, but the rate of increase slowed.(3) The Pearson correlation coefficient calculation revealed that rainfall intensity had a greater impact on soil erosion than slope. At 3° and 6° slopes, the field monitoring results were consistent with the laboratory test results, indicating that the indoor artificial rainfall simulation was suitable for studying runoff characteristics in karst areas. [Conclusion] The study provides theoretical guidance and technical support for soil erosion prevention and ecological restoration in the karst rocky mountain areas of northern Guangxi.