Due to the increase of the size of the gate hole and the thickening of the concrete floor and pier， the mutual restriction between the floor and pier is strengthened and the deformation coordination between them is reduced. It is easy to be affected by the external environment temperature， and it is easy to produce excessive tensile stress during the construction period and operation， and the situation of temperature control and crack prevention is severe. The primary task of temperature control and crack prevention of sluice gate is to determine the temperature control standard. However， the existing sluice gate design code only makes some principle provisions for the temperature control of sluice gate concrete， but does not give a detailed description of how to determine the temperature control standard. That is， the temperature stress control standard of sluice concrete is proposed first， then the permissible temperature difference of foundation and upper and lower layers is determined， and the maximum permissible temperature during construction is determined according to the quasi-stable temperature field of sluice structure. The temperature stress control standard of concrete of sluice structure can be determined by safety factor method， and it is recommended that the value of safety factor against cracking should not be less than 1.30. The value of stress constraint coefficient is calculated by the fitting formula given in this paper. Finally， taking a large orifice sluice in the Ganjiang River as an engineering case study， the corresponding temperature control standards are proposed. The research results can provide reference for the formulation of temperature control standards for a large orifice sluice.

Sand liquefaction caused by strong earthquakes is receiving increasing attention due to the frequency of extreme seismic events. The liquefaction possibility assessment is the primary task in the study of sand liquefaction. In this paper，a probability assessment model is established based on the field investigation of liquefaction cases，combined with the knowledge of probability statistics and logistic regression algorithm. The effectiveness of the model is verified by comparing with the existing deterministic liquefaction assessment methods. Furthermore，the parameters analysis affecting the liquefaction assessment results is also conducted. The results show that the liquefaction discrimination model established in this paper has a success rate of 85.70% and 82.50% for rejudging the liquefaction and non-liquefaction cases； and a success rate of 88.00% and 72.00% for the discrimination of the validation set， demonstrating a good discrimination success rate. The fine particle content， overburden stress correction factor，the correction coefficient for overburden stress，and the adjustment coefficient for seismic magnitude should be applied to correct case data when applying this model to assess liquefaction potential，which can improve the accuracy of sand liquefaction assessment.At the same time， the model can provide specific discrimination formulas. In the future， when new samples are incorporated， the model can be further improved by adjusting and modifying based on various parameters.

In order to master the dynamic characteristic index of asphalt concrete core wall， the dynamic characteristics of asphalt concrete core wall were taken as the research object. The dynamic triaxle test of asphalt concrete under the condition of setting temperature， consolidation ratio and confining pressure was carried out. The maximum dynamic modulus， damping ratio and modulus coefficient of asphalt concrete were sorted out by equivalent linear model， and the variation law and influencing factors of each index were analyzed. The test results show that the maximum dynamic modulus increases with the increase of confining pressure and consolidation ratio， the damping ratio decreases with the increase of confining pressure and consolidation ratio， the modulus coefficient K increases with the increase of consolidation ratio， and the exponent n decreases with the increase of consolidation ratio. In addition， the normalized empirical formulas of G_d/G_dmax and γ_d/γ_r were established， which can provide reference for the application of similar projects.

Corrosion-induced fracture of prestressed steel wires is one of the primary failure mechanisms in PCCP， with preventive measures and effectiveness evaluation being key focuses in durability research. To investigate the corrosion damage patterns of prestressed steel wires under stress-chloride coupling environments and identify effective anti-corrosion materials meeting durability requirements， this study examined the effects of applied stress on the corrosion behavior of bare wires in NaCl solutions at concentrations of 1%， 3.5%， 10%， and 20%， as well as single-component polyurea-coated wires in 3.5% NaCl solution， through open-circuit potential measurements， corrosion current density analysis， and electrochemical impedance spectroscopy， using stress-free conditions as the control group. For bare wires， chloride concentration predominantly governed corrosion progression， exhibiting the order： 3.5% NaCl > 1% NaCl > 10% NaCl > 20% NaCl. Stress only accelerated corrosion in low-concentration solutions. Regarding coated wires， applied stress accelerated coating resistance degradation， yet their corrosion current density remained five orders of magnitude lower than bare counterparts. After 25 days immersion under sustained load， the impedance modulus maintained 2.07×10⁷ Ω·cm²， demonstrating that single-component polyurea coating significantly enhances corrosion resistance of prestressed wires in stress-chloride coupling environments.

In hydropower station monitoring systems， fixed threshold methods are commonly used for over-limit alarms， but they exhibit low sensitivity in complex conditions， making early warnings difficult. This paper proposes a feature-enhanced anomaly detection （FEAD-DEGAN） model based on generative adversarial network discriminator and density estimation （DEGAN）. Convolution and global average pooling methods optimize the discriminator structure， enhancing time-series feature extraction. The dynamic threshold strategy and kernel density estimation improve detection sensitivity. The model is validated with abnormal oil head swing amplitude data from an axial-flow pump-turbine unit. Compared with Isolation Forest and Autoencoder， the proposed approach shows better performance in anomaly detection success rate and false alarm rate. SHAP quantifies the contribution of monitoring indicators to anomalies， identifying key factors that influence abnormal behavior and enhancing process interpretability. This supports root cause analysis and facilitates the optimization of maintenance strategies， thereby contributing to more effective fault diagnosis and intelligent maintenance.

The construction of Low Impact Development （LID） facilities has a significant impact on alleviating urban waterlogging disasters. To study the effect of LID facility construction on rain and flood control in the northern plain area， this paper constructs a Storm Water Management Model （SWMM） based on the district as the base of the central urban area of Hengshui city， analyzes the current pipe network flow capacity， and simulates and compares the rain and flood control effects before and after the construction of LID facilities in the central urban area from the aspects of annual total runoff control rate and flood risk. The simulation results show that the drainage capacity of the central part of each area in the central urban area is relatively lower than that of the surrounding areas. More than 50% of the pipe network has a good drainage capacity， but about 30% of the pipe network still needs to be renovated. After the construction of LID facilities， the annual total runoff control rate in the central urban area has significantly increased to 76%， an increase of 14% compared with the development and construction before. The annual total runoff control rate of each key district has reached more than 75%. By comparing the flood risk in the built-up area of the central urban area under a 30-year return period 24-hour rainfall （cumulative rainfall of 195.7 mm） before and after the construction of LID facilities， the flood risk area has decreased by 4.46 km² after the construction， and all 8 severe flood waterlogging points that appeared before have been eliminated. The flood prevention standard area is about 71.59 km²， accounting for 93.3% of the built-up area， and the flood prevention standard area has reached the standard. The construction of LID facilities in the central urban area can effectively cope with a 30-year return period of heavy rain.

Flood and debris flow occur frequently in mountain streams - due to multiple factor such as landslides， loose solids， and heavy rainfall. Their carrying of sediment， rocks， driftwood， and other debris obstructs road embankment and bridge culverts， amplifying the magnitude of flood disasters and seriously troubling flood prevention efforts. Based on the investigation of flash flood and debris flow disasters in the Zhenghe River basin of Beichuan County in Sichuan Province and by combing the types of floods and the debris jam characteristics of culverts， the process of floods and debris flow， as well as the maximum flow depth and flow velocity characteristics under six disaster scenarios， are investigated using numerical simulation approach. The dynamic factor v^{\mathrm{2}}d （where v is the flow velocity and d the flow depth）， is introduced as an index of the intensity of the external load acting on buildings or disaster-bearing bodies to divide floods and debris flow risk zones and determine the level of hazard. The findings demonstrate that there are significant differences in the spatial distribution of the maximum depth and flow velocity under the six simulation scenarios of flood and debris flow. The scenario of culvert blockage has the smallest difference between simulated and measured flood marks in mud depth. The hazard grades can well represent the actual degree of damage to buildings the amplification effect of flow and the diversion of the main flow caused by the blockage of road embankment and bridge culverts are the main reasons for the amplification of disaster-affected areas. The research results can provide an important reference for disaster prevention and reduction planning in mountainous areas， the assessment of building location and structural type， the selection of temporary safe evacuation sites， and potential risk investigation ， etc.

The long-term over-extraction of groundwater in Hengshui City has led to a continuous decline in the deep groundwater levels， which in turn has caused serious ground subsidence issues， threatening the sustainable development of the regional economy and ecological environment. Studying the distribution characteristics of ground subsidence and its response relationship with deep groundwater levels is of great significance for preventing and controlling subsidence disasters and formulating scientific policies for groundwater development and utilization. This study is based on SBAS-InSAR data and deep groundwater level monitoring data from 2018 to 2022. It analyzes the characteristics of ground subsidence in Hengshui City and its response relationship with deep groundwater level changes across three time scales： multi-year averages， inter-annual variations， and monthly fluctuations. Using the cross-wavelet transform analysis method， this research quantitatively investigates the periodic characteristics of ground subsidence and deep groundwater level evolution and their time-lag relationships at representative points. The research results indicate that： （1） From 2018 to 2022， Hengshui City was in a state of subsidence as a whole， with areas that have a cumulative subsidence of over 100 mm accounting for 86.54%. This has formed two distinct subsidence zones， one stretching from Raoyang to Shenzhou and the other at the junction of Jizhou-Zaoqiang to the boundary between Fucheng County and Jingxian County. （2） The study area was in a “rapid subsidence” phase from 2018 to 2019， with the highest subsidence intensity occurring in Anping County and Raoyang County. After 2020， it entered a "slow subsidence" phase， where the recovery of deep groundwater levels significantly slowed down the subsidence rate. By 2022， the average subsidence amount decreased to 4.7 mm. However， some areas continued to experience further subsidence as their groundwater levels were lower than the historical minimum groundwater levels. （3） The groundwater level falling below the historical minimum groundwater levels is a key driving factor for subsidence， and the resulting inelastic compression is the main component of the subsidence amount. This indicates that preventing deep groundwater levels from falling below historical lows is an effective measure for controlling ground subsidence. （4） The average time lag between ground subsidence and changes in groundwater levels at six representative points is 38.83 to 66.99 days， demonstrating a significant lag effect in the compaction of aquifers in the area. The findings of this study can provide a scientific basis for subsidence prevention and control， water resource management， and regional sustainable development in the Hengshui area.

Mountain river floods pose a serious threat to the safety of foothill urban areas. Constructing flood detention and storage zones in front of mountainous regions can retain floodwater，reduce flow velocity，attenuate flood peaks，and effectively mitigate the impact of floods on developed areas. Taking the Beisha River in the Wenyu River Basin，Beijing，as a case study，this research employs a numerical simulation method based on hydrodynamic principles to simulate the flood evolution processes under two scenarios： free flood discharge and discharge regulated by flood detention zones. By comparing the flood risks and spatial distributions under different return-period floods before and after the construction of detention zones，the effectiveness of flood control and disaster mitigation was evaluated.The results indicate that： under various return-period flood scenarios，the foothill detention zones along the Beisha River can significantly reduce downstream flood peaks，inundation extent，and water depth，thereby lowering regional flood risk； the overall mitigation effect is constrained by the scale of the detention zones — under the 20-year flood scenario，the Beisha River detention zone achieves the highest mitigation benefit，reducing GDP losses by 27.55%，followed by 22.45% under the 50-year design flood； numerical simulation of flood processes provides an effective means to quantitatively analyze and assess the mitigation performance of planned or ongoing flood control projects，through comparative analysis of flood risks before and after project implementation.

In the identification of operational behavior of earth pressure cells and structural safety assessment， measurement gross errors often coexist with abrupt changes reflecting actual structural responses， thereby compromising the accuracy of safety evaluation. To address this issue， this paper proposes an anomaly detection method for earth pressure cell measurements based on frequency domain decomposition and multi-point joint analysis. Through decomposition and reconstruction in the frequency domain， frequency components representing long-term trends and short-term fluctuations are derived. Subsequently， by integrating correlation analysis and the Isolation Forest algorithm， joint anomaly detection and diagnosis across multiple measurement points are achieved. Case studies based on actual engineering monitoring data demonstrate that the proposed method can accurately distinguish between gross errors and abrupt changes caused by structural anomalies or environmental factors， with high detection accuracy. The method enhances the diagnostic capability of earth pressure cell measurements and improves structural safety monitoring.

In coastal area of China， there are many aquifers widely distributed in the soil layer， which need dewatering in the process of excavation construction. If it is easy for water to leak between different aquifers， and difficult to fully block the hydraulic connection between inside and outside the excavation， it will cause a large change of water level outside the excavation in the process of dewatering， leading to a series of environmental problems. Therefore， the deformation pattern and control method caused by the dewatering in multi-aquifer leaking excavation are worthy of further study. Based on the dewatering test results of the excavation of a subway station in Tianjin， this paper adopts the finite element method to study the influence of silt lens and leaking aquifers on the excavation deformation in the toe soil layer of the diaphragm wall induced by dewatering. Moreover， the mechanism of influence of silt lens on dewatering induced deformation and the comparative study of deformation induced by different dewatering schemes are also conducted. The results show that hydraulic connection between the upper and lower aquifers at the depth of the toe of the diaphragm wall can reduce the deformation of the diaphragm wall while increasing the settlement outside the excavation. The mechanism behind this is that the hydraulic connection reduces the pore pressure difference between the sides of the diaphragm wall， but increases the drawdown outside the excavation. In this case， it is recommended to adopt the “deep and shallow well” dewatering system with independent filters for the phreatic and confined aquifers， along with timely installation of horizontal supports. Dewatering should be implemented as needed to control the deformation induced by the dewatering process.

In response to the demand for termite prevention in hydraulic engineering， this study constructed a predictive model for termite habitat suitability in Zhejiang Province by integrating the MaxEnt ecological niche model with GIS spatial analysis technology， based on termite census data from Zhejiang Province’s hydraulic engineering projects （2023-2024）. The research systematically revealed the spatial distribution patterns and environmental driving mechanisms of termite habitats in Zhejiang Province. Through a dynamic screening process of “preliminary selection-contribution analysis-collinearity test-iterative optimization”， 22 initial environmental factors were refined to 14， achieving a model AUC value exceeding 0.963. The Jackknife test identified soil pH （6.0-6.4）， annual precipitation （1280-1450 mm） and elevation （80-200 m） as the core environmental drivers most suitable for termite survival in hydraulic engineering. Spatial simulations indicated that the total area of termite-suitable habitats in Zhejiang Province is 40，300 km²， with high-suitability zones （6 400 km²） concentrated in the hilly valleys of central and southern Zhejiang， medium-suitability areas （13，700 km²） distributed in patches in central and northern Zhejiang， and low-suitability zones （20，200 km²） covering all river basins in the province with potential diffusion risks. The research not only provides a reusable technical paradigm for biological disaster risk assessment in hydraulic engineering but also offers important references for formulating precise "one-reservoir-one-policy" prevention systems， guiding the layout of monitoring stations， prioritizing prevention efforts， and developing ecological barrier technologies.

Using portable CO₂ detectors to locate tunnel entrances and nests of the subterranean termite Odontotermes formosanus （Shiraki） in agricultural， forestry， and water conservancy facilities facilitates rapid nest localization and enables scientific control measures.Using a special portable carbon dioxide detection device， the detection area was set up in the serious occurrence plot of O. formosanus. The device was used to detect the ground carbon dioxide concentration， and the concentration anomaly point was excavated to verify the nests and nests entrance of O. formosanus. In addition， the carbon dioxide gas source point at the entrance of the simulated termite nest was set up to determine the concentration diffusion range of carbon dioxide under different wind speeds and wind directions. The device used in the environment with atmospheric wind speed of 0~0.12 m/s can quickly detect abnormal points of carbon dioxide concentration （ termite nest entrance， decayed dead wood or leaves ）. After excavation， it is confirmed that the carbon dioxide concentration at the entrance of the ant road is above 0.10%. In simulations of the carbon dioxide gas source， at wind speeds of 0， 0.1， 0.2， 0.4， 0.8， 1.6， and 3.2 m/s， the downwind distance from the source point to where the CO₂ concentration reaches 0.05% is 0.4， 1.0， 1.0， 0.6， 0.4， 0.2， and 0 m， respectively. The distance from the site with a concentration of more than 0.05% in the crosswind direction to the gas source point is 0.4， 0.4， 0.2， 0.2， 0 and 0 m， respectively. The distance between the abnormal site of carbon dioxide concentration and the gas source point is significantly affected by wind direction and wind speed. The portable carbon dioxide detection device can easily detect the abnormal value of carbon dioxide concentration at the entrance of the termite nest in the termite occurrence site. Combined with wind speed， wind direction， measuring point distance， etc.， the position of the O. formosanus nests entrance can be quickly detected after eliminating interference factors.

Soil-dwelling termites that excavate tunnels and construct nests within embankments represent one of the most critical latent threats to hydraulic engineering. Consequently，accurate and efficient localization of termite nests is essential for effective prevention and control. This study，grounded in the biological behavioral patterns of termites，presents a novel localization approach that integrates deep learning-based object detection with probabilistic field modeling. First，an enhanced YOLOv5 architecture is developed to automatically identify termite castes，including soldiers，workers，and nymphs. Second，an improved multi-object tracking framework based on DeepSORT is employed to generate counting zones for each caste，quantify their populations，and determine aggregated dominant movement directions. Finally，leveraging the characteristic foraging distances and activity distributions of the three castes，a behavioral-habit-based probabilistic model is constructed. This model incorporates dynamic distance and direction weighting functions to generate a two-dimensional probabilistic field centered on each bait-recognition point. The feasibility of the proposed method is validated through experimental comparisons between predicted and actual nest locations. Furthermore，by applying global probability extension and likelihood fusion，the framework supports multi-point matrix-based cooperative localization. Integrating computer vision，ecological behavior analysis，and probabilistic modeling，the method provides a low-cost，high-efficiency alternative to traditional techniques，with scalability for large-scale data analysis and compatibility with IoT-based remote monitoring systems，thereby substantially enhancing the efficiency of termite nest localization.