[Objective] The aim of this study is to address the issue of stability control of surrounding rocks during the construction of underground oil storage caverns. [Methods] We first clarified the types and manifestations of surrounding rock instability in caverns, and then applied the block theory to analyze the issues of block identification and stability caused by unfavorable combinations of structural planes. The key blocks identified during construction period were classified based on their geometric shapes, and key blocks requiring support were selected according to their morphological types. Subsequently, we focused on the identification of hazard-causing blocks during construction to analyze key issues such as the identification of cross-layer blocks (which only become fully exposed after multi-layer excavation in high-sidewall caverns), instability characteristics of surrounding rocks involving along-cavern joints, and potential instability risks at the intersections of caverns. [Results] Using block theory to determine whether different combinations of structural planes could form key blocks, followed by stability and support analysis, serves as a necessary supplement to the conventional approach relying on surrounding rock quality classification for support design. The geometric shapes of blocks were classified into three types: “regular-shaped”, “flat and shallow-buried”, and “sharp and deeply embedded”, with the “regular-shaped” blocks being the primary type requiring support. “Flat and shallow-buried” blocks were prone to spontaneous falling, “sharp and deeply embedded” blocks were less likely to become unstable, and “regular-shaped” blocks required support, thereby providing a basis for differentiated support during the construction period. Based on the distribution characteristics of blocks during the construction period, the key issues of the identification and control of hazard-causing blocks were summarized as follows: (1) cross-layer blocks were the main hazard sources during the construction of high-sidewall caverns. It was necessary to splice and compare geological sketches obtained from multiple excavation layers to analyze the cross-layer extension characteristics and intersections of structural planes to determine whether cross-layer blocks may form. (2) Along-cavern joints, due to their limited visible exposure and “concealed” characteristics, were prone to form collapse blocks when intersecting with other structural planes in hard rock sections, while in medium to soft rock sections, they may cause large-scale sliding instability. (3) At cavern intersections, the increase in free surfaces, along with fewer structural plane cuts, may still result in the formation of hazard-causing blocks, thereby increasing safety risks. [Conclusion] The findings advance the understanding of block identification and stability analysis during the construction of underground caverns. The proposed classification of block shapes and the summarized key issues in recognizing hazard-causing blocks can provide a reference for the stability control of surrounding rocks in similar cavern engineering projects.
[Objective] This study systematically examines the characteristics of sediment deposition and river evolution in Lushui Reservoir over 60 years since its construction and evaluates their comprehensive impacts. [Methods] Based on pre-construction (1959) 1∶10 000 topographic maps and recent (2018) 1∶5 000 maps, sediment volumes and stage-capacity curves were calculated using the cross-section method and 10 m × 10 m grid-based method (combined with Simpson’s 3/8 rule). [Results] The total deposition was 32.397 million m3, accounting for only 4.6% of the total storage below the design flood level, indicating overall light siltation. However, the spatial distribution was highly uneven—74% of the deposition was concentrated below the flood-limit water level, with the Hongshang-Shikeng downstream 11km reach becoming the core deposition zone, accounting for 51% of the total (local maximum deposition thickness up to 11.79 m), while the Hongshang-Langkou reach was likely in a scouring state due to unregulated sand mining and reduced sediment inflow. For channel evolution, the thalweg in the Hongshang-Shikeng reach rose on average 6.27 m, and the shoreline at the 45 m dead water level elevation shrank markedly; maximum thalweg migration reached 660 m (at the Lashupu widening), and the depositional pattern tended toward a deltaic form—with the Hongshang-Shikeng reach dominated by main-channel deposition, and sections above Hongshang mainly showing floodplain deposition. Deposition significantly impaired reservoir functions: (1) For flood control, 6.856 million m3 of flood-control capacity was lost (4.2% loss rate), and the cross-section area in the Hongshang-Shikeng reach was reduced by 26% on average (up to 54%), markedly lowering discharge capacity and raising the regulated flood levels under design floods. (2) For beneficial use, 17.193 million m3 of active storage lost (equal to an annual power loss of 842 000 kW·h), and 12.29 million m3 between the dead water level and flood-limit level was lost (8.1% of mean annual irrigation withdrawal). (3) For navigation, thalweg elevations were generally at or above the 45 m dead water level elevation, severely restricting navigation during low-flow periods. [Conclusion] Although the overall sedimentation rate of Lushui Reservoir is low, local deposition poses a significant threat to flood-control and navigation functions. Mechanical dredging in the key reach (Hongshang-Shikeng) and optimization of sediment-flushing schedules during the flood season are urgently needed to control sediment and maintain effective storage capacity. These findings provide a scientific basis for sediment management in long-operating reservoirs and for the development of “modern reservoir operation and management matrix” proposed by the Ministry of Water Resources.
[Objective] Scientifically and efficiently protecting and utilizing river sand resources is fundamental to ensuring stable economic, social, and ecological development. [Methods] This study systematically collected and organized data related to sand mining management in the Pihe River, supplemented by field investigations, site inspections, and theoretical analysis, to examine the current management status and identify problems and challenges in regulatory supervision. [Results] Sand mining management of the Pihe River faced the following problems: incomplete and low-quality data for the formulation of sand mining plans; inconsistent quality in the implementation plans across counties and districts, with some merely replicating the original planning documents; differing supervision approaches and standards among municipalities, districts, and counties along the river, indicating the need for improved joint oversight; limited tools to regulate and monitor the minimum excavation elevation; and inadequate sand mining data management in some areas, where records remained largely paper-based and unstandardized. Measures and proposals were put forward to strengthen the supervision of river sand mining, including enhancing the preparation of sand mining plans, scientifically formulating implementation plans, establishing joint supervision mechanisms across municipalities, districts, and counties, strengthening whole-process management of sand extraction and transport, and standardizing sand mining data management. [Conclusion] Future efforts should focus on: (1) establishing a coordinated sand mining management mechanism, led by governments at or above the county level, with water authorities taking the lead, coordinated by relevant departments, and subject to public supervision, to strengthen integrated management; (2) enhancing whole-process supervision of sand mining activities before, during, and after extraction; (3) promoting the application of new technologies, such as BeiDou monitoring systems for river sand mining, electronic documentation for sand transportation, electronic sand mining permits, artificial intelligence, and the Internet of Things. The findings can serve as a reference for sand mining management in rivers nationwide and support lawful, scientific, and standardized sand extraction.
[Objectives] This paper aims to provide theoretical basis and scientific support for the prediction, early warning, and systematic prevention and control of riverbank collapse in the middle reach of mainstream Yangtze River by reviewing the characteristics and mechanisms of riverbank collapse. [Methods] By reviewing domestic and international literature, we systematically summarize current research status of riverbank collapse along the middle reach of mainstream Yangtze River, including the definition, classification, spatiotemporal distribution characteristics, and main influencing factors and their action mechanisms. Using measured data from hydrological stations including runoff, sediment load, and water level variations, we analyze the changes in water and sediment conditions before and after the operation of the Three Gorges Reservoir and their impacts on bank collapse. Particular focus is given to the mechanisms of bank collapse from both internal factors (such as the properties of riverbank soil and channel morphology) and external factors (such as hydrological and sediment conditions, water level fluctuations, vegetation coverage, and human activities). [Results] Spatiotemporal distribution characteristics: riverbank collapse along the middle reach of mainstream Yangtze River exhibits variation both longitudinally and laterally along the river; the frequency of collapse in the lower Jingjiang section is higher than that in the upper Jingjiang section, and collapses occur more often on the left bank than on the right bank. Affected by water scouring and water level fluctuations, the flood season and the recession period after the flood are peak periods for bank collapse. After the operation of the Three Gorges Reservoir, the number of river sections with strong catastrophic bank collapse decreases significantly. Internal factors of bank collapse include the composition of riverbank soil (such as the binary structure of an upper cohesive soil layer and a lower sandy soil layer), the height difference between the beach and the trough, channel sinuosity, and bank slope gradient. External factors include water and sediment conditions (such as longitudinal flow scouring, circulation erosion, and backflow scouring), water level fluctuations, vegetation coverage, and human activities (such as near-bank sand mining, sudden loading, and slope excavation). Water flow scouring is the dominant factor of bank collapse, especially the scouring effect of longitudinal flow, which directly impacts the riverbank crest and slope. Meanwhile, circulation erosion, backflow scouring, and water level fluctuations also jointly contribute to the occurrence of bank collapse. Bank protection projects achieve significant results in controlling collapse, but collapse still occasionally occurs in protected sections. Bank protection work does not significantly change the flow structure, but intensifies scouring at the unprotected toe of the slope, resulting in deep troughs approaching the bank and further aggravating riverbank erosion. [Conclusions] Bank collapse is the result of the combined effects of multiple factors. It remains necessary to conduct in-depth research on the characteristics of riverbank collapse in the middle reaches of the Yangtze River and to clarify the threshold values of influencing factors, to provide a reference for slope stability assessment and for the prediction and early warning of bank collapse. During design and construction, attention should be paid to controlling the underwater slope gradient of engineering works and to considering the impact of toe scouring on the overall stability of the riverbank. With the continued operation of hydropower stations such as Wudongde and Baihetan in the lower reaches of the Jinsha River and the ongoing implementation of soil and water conservation efforts in the basin, the “clear water scouring” in the middle and lower reaches of the Yangtze River will persist. Therefore, priority should be given to preventing bank collapse caused by strong longitudinal scouring and channel pattern adjustment in highly sinuous river sections, and to strengthen protection, routine monitoring, and early warning in these areas. Future research may further explore the effect of vegetation in stabilizing riverbanks, and enhance monitoring of river morphology, the stability of specific cross-sections, and channel evolution, in order to increase the inspection frequency and monitoring precision in high-risk reaches and areas prone to collapse.
[Objective] This study aims to conduct a comprehensive evaluation of the ecological benefits of the South-to-North Water Diversion Project (SNWDP) by systematically quantifying the ecological benefits in the water-receiving areas during the first phase of the Middle Route Project. [Methods] The water receiving area was divided according to administrative units and assessed using statistical and remote sensing data. Taking 2014 as the base year and 2018, 2020, and 2023 as evaluation years, we evaluated the ecological benefits brought by project-supplied water in Beijing, Tianjin, 11 counties (or cities) of Henan, and 6 counties (or cities) of Hebei. Ecological benefit index systems were established for forest land, urban green space, wetlands, water bodies, and groundwater ecosystems by integrating the function value method and the equivalent factor method. For forest land, urban green space, and groundwater ecosystems, multiple ecosystem service functions were quantitatively analyzed. The market value method, replacement cost method, and other valuation methods were used to estimate the unit prices of each function and calculate their total service value. For wetlands and water body ecosystems, ecological benefits were calculated using the equivalent factor method based on regional characteristics. A spatiotemporal precipitation adjustment factor was introduced to dynamically adjust the factor values in the basic equivalent factor table, thereby determining the value of one standard unit of ecosystem service equivalent factor. [Results] Cumulative ecological benefits generated by the water supply from the first phase of the Middle Route Project amounted to 44.859, 18.328, and 37.102 billion yuan in each evaluation period, respectively. Wetlands and water bodies accounted for the largest proportions, at 64.90%, 58.98%, and 46.98%, respectively. From 2015 to 2018, new ecological benefits from water bodies and wetlands reached 24.724 and 4.391 billion yuan, respectively; for 2019-2020, they were 9.100 and 1.709 billion yuan; and from 2021 to 2023, new ecological benefits from wetlands and water bodies were 11.079 and 6.352 billion yuan, respectively. The annual average new ecological benefits for each period were 11.215, 9.164, and 12.367 billion yuan, indicating that the project’s water supply generated approximately 10 billion yuan of ecological benefits per year in the water receiving areas. In addition, the ecological benefit value per cubic meter of water varied across provinces and cities. In Beijing, the values were 1.64, 1.38, and 3.01 yuan; in Tianjin, 3.34, 2.19, and 0.52 yuan; in Henan’s 11 counties, 8.16, 5.06, and 3.79 yuan; and in Hebei’s 6 counties, 6.12, 2.69, and 4.07 yuan, respectively. The benefit value ratios for Beijing∶Tianjin∶Henan∶Hebei in each evaluation period were 1∶2.10∶4.99∶3.74, 1∶1.59∶3.66∶1.95, and 1∶0.17∶1.26∶1.35, respectively. [Conclusion] This study provides a case reference for ecological benefit evaluation the follow-up projects of the SNWDP and other inter-basin water diversion projects. It provides technical support for the scheduling and utilization of ecological benefits of the Middle Route Project, and further provides a calculation basis for promoting the establishment of horizontal ecological compensation standards between the water receiving and source areas.
[Objective] This study aims to reveal the influence mechanisms of hydrothermal conditions on the spatiotemporal variability of hyporheic exchange and to develop more reliable estimation methods. We acknowledge the limitations of single methods and innovatively propose an estimation framework for hyporheic exchange that integrates hydraulic methods, environmental tracer methods, and numerical simulation technologies. The proposed method is expected to address the insufficient accuracy and scale mismatch in existing estimation methods and to enhance the capacity to quantify highly variable hyporheic exchange fluxes. [Methods] First, based on years of practical experiences, and combined with a systematic review and critical analysis of existing literature, we deeply analyze the intrinsic driving mechanisms of the spatiotemporal variability of hyporheic exchange from two core perspectives: hydraulics and thermodynamics. Second, we propose an integrated multi-method estimation framework to improve the accuracy and robustness of the estimation results. [Results] The mechanisms by which hydrothermal conditions drive the spatiotemporal variability of hyporheic exchange are summarized as follows.(1) Hydrological rhythm: the dynamic variations in river water level and discharge alter the hydraulic head difference between river water and groundwater, serving as the primary driver of the temporal changes in the rate and direction of hyporheic exchange.(2) Topography, geomorphology, and bed heterogeneity: local topographic features of rivers and lakes (such as sand bars, pools, and point bars) and the spatial heterogeneity of riverbed sediments shape the spatial distribution pattern of hydraulic head differences, which is the fundamental cause of significant spatial variations in hyporheic exchange.(3) Temperature variation: strong daily temperature differences can generate significant thermal gradients within riverbed sediments, inducing rapid flows and shaping the diurnal variation patterns of hyporheic exchange.(4) Seasonal freezing and thawing processes substantially alter the spatial structural characteristics of riverbed permeability, profoundly affecting both the intensity and spatial extent of hyporheic exchange at seasonal and spatial scales. These driving factors are often in a state of nonstationary variations and exhibit complex couplings. Collectively, their combined effects make the spatiotemporal variation patterns of the hyporheic exchange difficult to be accurately captured or predicted by simple methods. [Conclusion] This study systematically elucidates the mechanisms by which hydrothermal conditions jointly influence the complex spatiotemporal variations of hyporheic exchange through hydraulic and thermodynamic processes. It deepens the understanding of surface water-groundwater interactions, providing a theoretical basis and practical guidance for developing more accurate watershed hydrological models, assessing the health of river ecosystems, and formulating science-based ecological restoration strategies for rivers and lakes.
[Objective] To address the low accuracy of monthly runoff point prediction and the difficulty in describing the uncertainty of point prediction results, this study proposes a monthly runoff point prediction model and an interval prediction model based on the Crested Porcupine Optimizer (CPO), Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM) network, and Nonparametric Kernel Density Estimation (NKDE). [Methods] First, a hybrid point prediction model (CPO-CNN-BiLSTM) was developed. CPO was used to optimize key model parameters such as the number of hidden layer nodes, initial learning rate, and regularization coefficient. Monthly runoff data and its influencing factors were input to the model to obtain point prediction results. Next, the point forecasts were sorted using a range segmentation method and divided into low, medium, and high flow segments. The relative error for each predicted value within these segments was calculated. The NKDE method, with window width optimized by CPO, was employed to estimate the error probability distribution function for each segment. Cubic spline interpolation was then applied to fit the probability distribution functions of the three segments and derive segment-specific quantiles, forming a monthly runoff interval prediction model (CPO-CNN-BiLSTM-NKDE) based on NKDE method and the CPO-CNN-BiLSTM model. Finally, the runoff point forecasts were combined with the corresponding quantiles of their flow segments to generate monthly runoff interval predictions. Case studies compared the proposed CPO-CNN-BiLSTM point prediction model with traditional models including Least Squares Support Vector Machine (LSSVM), Kernel Extreme Learning Machine (KELM), LSTM, and BiLSTM, using RMSE, MRE, and MAPE as evaluation metrics. [Results] The CPO-CNN-BiLSTM model’s prediction accuracy was significantly better than the other models, especially during flood and dry seasons. Compared with the best-performing among the other four models in terms of RMSE, MRE, and MAPE, the values decreased by 43.71%, 38.56%, and 24.38%, respectively. This indicated a superior ability to accurately predict peak and valley runoff values. Additionally, deep learning models (LSTM, BiLSTM, CNN-BiLSTM) outperformed machine learning models (LSSVM, KELM), with the BiLSTM model surpassing LSTM, and the CNN-BiLSTM hybrid outperforming both. The proposed CPO-CNN-BiLSTM-NKDE interval prediction model was compared with other interval prediction models at confidence levels of 95%, 90%, and 85%, and it exhibited the highest Prediction Interval Coverage Probability (PICP)and the lowest Prediction Interval Normalized Average Width (PINAW), indicating strong reliability and superior capability in capturing uncertainty. This demonstrated that the interval prediction results of the proposed model could help decision-makers better understand and respond to the uncertainty and variability in the data. [Conclusion] The proposed CPO-CNN-BiLSTM point prediction model and the CPO-CNN-BiLSTM-NKDE interval prediction model effectively address the challenges posed by the spatial-temporal complexity of monthly runoff sequences and the uncertainty of monthly runoff point predictions. This provides new ideas for monthly runoff prediction and offers useful reference for fields such as wind speed and solar irradiance forecasting.
[Objective] Dianchi Lake, an important freshwater lake in Southwest China, has experienced increasing water quality degradation and eutrophication in recent years due to urbanization and agricultural activities. Most existing studies primarily focus on interannual variations, with limited understanding of seasonal variation and spatial heterogeneity. This study aims to: (1) reveal the spatiotemporal distribution patterns of water quality in Dianchi Lake using the Water Quality Index (WQI) method; (2) evaluate eutrophication dynamics using a logarithmic power-function universal index; and (3) identify key driving factors to provide scientific support for targeted remediation strategies. [Methods] Using daily water quality data from 2021 to 2023 at ten nationally controlled monitoring stations in Dianchi Lake, the WQI—incorporating six indicators (TP, TN, CODMn, NH3-N, DO, and turbidity)—was employed to classify water quality levels. Eutrophication Index (EI) calculated using the logarithmic power function model including Chl-a, TN, TP, and CODMn, was applied to evaluate eutrophication levels. Spatial patterns were depicted using Kriging interpolation in ArcGIS, and correlation analysis was conducted to identify the major influencing factors. [Results] 1) Spatiotemporal characteristics of WQI: (a) regarding temporal variations, the mean WQI was 65.03 (ranging from 31.33 to 82.67), with “moderate” water quality prevailing. Water quality was poorest in summer (only 16% rated “good”), primarily due to high temperatures accelerating organic decomposition, leading to decreased DO (8.40 mg/L) and increased CODMn (6.29 mg/L). Water quality was best in winter. (b) In terms of spatial variations, the average WQI in Caohai (68.96) was significantly higher than that in the Waihai (64.01), attributed to nutrient absorption by wetland vegetation. Severe pollution accumulation was observed in the central Waihai (e.g., Guanyinshan monitoring station) due to limited water exchange. 2) Dynamics of EI: (a) for seasonal patterns, eutrophication was most severe in spring, with an average EI of 55.166, and 16.8% of the area reached a “moderate eutrophication” level, due to runoff inputs during the peak agricultural fertilization season. Summer exhibited the greatest variation in EI (38.102-87.603), accompanied by frequent algal blooms. (b) In light of spatial differentiation, EI values in Caohai were generally higher than those in Waihai,particularly at Duanqiao and the center of Caohai, where direct urban sewage discharge was significant. In northern Waihai, areas such as Luojiaying exhibited higher eutrophication levels due to intensive human activities. 3) Key driving factors: (a) WQI was strongly positively correlated with DO (+0.492), and negatively correlated with NH3-N (-0.485) and CODMn (-0.358), indicating that organic pollution primarily drove water quality variation. (b) EI was mainly influenced by TP (with a weight of 0.230) and Chl-a (0.326), suggesting that phosphorus control and algae management were crucial for mitigating eutrophication. [Conclusions] Dianchi Lake exhibits pronounced seasonal and spatial heterogeneity in both water quality and eutrophication. In summer, nonpoint source pollution should be strictly controlled, while in spring, agricultural fertilization should be limited. The ecological restoration experiences in Caohai could be extended to Waihai, and enhanced water circulation is needed in the deep-water central zone. This study innovatively integrates the WQI and EI models, establishing a replicable methodological framework for dynamic assessment of eutrophic lakes, and emphasizes the need for long-term monitoring data to refine management strategies.
[Objective] This study aims to propose a novel method for predicting effluent water quality in wastewater treatment plants, in order to enhance prediction accuracy and address the inadequate generalizability of existing models, thereby providing robust support for the operational optimization of wastewater treatment plants. [Methods] The proposed prediction framework primarily includes the following steps: First, the water quality sequence was decomposed into multiple subsequences with different characteristics using the variational mode decomposition (VMD) method. Subsequently, a comprehensive evaluation indicator (CEI) was introduced, based on which the deep learning algorithm with optimal prediction performance was selected for each decomposed subsequence. Four deep learning algorithms were involved in this study. Finally, the predicted values from each sub-model were aggregated to obtain the final effluent quality prediction. Taking the effluent chemical oxygen demand (COD) concentration of a wastewater treatment plant in Wuhan, Hubei Province as the research object, the proposed prediction framework was validated through a case study. The performance of the proposed framework was evaluated by comparing the prediction performance with that of single models. [Results] The effluent COD concentration data from a wastewater treatment plant in Wuhan were used for validation. The results showed that by decomposing the COD time series into different intrinsic mode functions (IMFs) using VMD, the complexity of the COD time series was effectively reduced. This provided simplified components for subsequent prediction, enabling the prediction model to better capture underlying patterns in the data and consequently improve prediction performance. Meanwhile, by introducing the CEI, four key evaluation indicators—mean absolute error (MAE), root mean square error (RMSE), standard deviation (STD), and mean absolute percentage error (MAPE)—were successfully integrated. This allowed for a comprehensive consideration of multi-dimensional error conditions when selecting the optimal prediction algorithm for each IMF subsequence, ensuring the comprehensiveness and accuracy of the selected algorithm. Finally, predictions were made for each different IMF based on the selected algorithm with optimal prediction performance. The results showed that this method effectively improved the overall model’s prediction accuracy, with the RMSE reaching 0.485. This confirmed that the proposed prediction framework achieved significant improvement in prediction performance compared to single models, providing strong support for accurate effluent water quality prediction in wastewater treatment plants. [Conclusions] The proposed water quality prediction framework based on VMD and multiple deep learning algorithms achieves high-precision prediction of effluent COD concentration in wastewater treatment plants by reasonably decomposing the water quality sequence and adaptively selecting prediction algorithms. The framework overcomes the limitations of existing single prediction models in handling complex nonlinear relationships, providing more accurate water quality predictions to support energy-saving and consumption-reduction decision-making in wastewater treatment plants. With significant practical value, it can be further extended in the future to predict other water quality indicators and be applied to wastewater treatment plants of different scales and types, thereby promoting intelligent operation and management in the wastewater treatment industry.
[Objective] The Hanzhong section of Hanjiang River is an important water source for the “South-to-North Water Diversion” and “Hanjiang-to-Weihe Diversion” projects. Its water quality directly affects the ecological environment and residents’ production and livelihoods along these water transfer systems. This study aims to analyze the current pollution status of heavy metals in Hanzhong section, explore their spatiotemporal distribution characteristics, and identify their primary sources. [Methods] Based on 240 sets of measured data of seven heavy metals (Hg, Pb, Cu, Zn, As, Cd, Cr) and four conventional monitoring indicators (pH, DO, NH3-N, CODCr) collected from 20 sampling sites in Hanzhong section from January to December 2022, we analyzed the temporal differences of heavy metal pollution during wet season (July-September) and dry season (December-February) using an improved heavy metal pollution index (HPI). The Nemerow comprehensive pollution index was used to evaluate the current pollution status of heavy metals in the water bodies, with reference to the Class I surface water quality standard. Pearson correlation analysis and principal component analysis were jointly applied to investigate the correlations among heavy metals and between heavy metals and conventional indicators, and to identify their main pollution sources. [Results] The annual average concentrations of seven heavy metals in this river section followed the order: Zn>Cr>Cu>Pb>As>Cd>Hg, all within the Class II standard limits of GB 3838—2002. Spatially, high-concentration cross-sections mainly distributed around mining and metal smelting enterprises. Temporally, the HPI index during wet season was slightly higher than that during dry season, but neither exceeded the critical threshold. At some urban traffic arteries, due to traffic pollution and atmospheric deposition, the pollution index during dry season was relatively higher. The single-factor pollution index evaluation results indicated that Cu and Cr were primary pollution factors, followed by Hg and Zn. Correlation analysis results showed that Cd had highly significant positive correlations with Pb, Zn, and As. As was highly significantly positively correlated with Pb and Zn, and Zn was highly significantly positively correlated with Pb. Hg, Zn, Pb, Cu, As, and Cd had significant positive correlations with NH3-N, suggesting that they had the same sources. Principal component analysis results revealed that the first principal component, including Pb, Zn, As, Cd, and Hg, was mainly affected by industrial sources, transportation, and domestic sewage discharge. The second principal component, including Cr, Hg, and Cu, was mainly affected by industrial and agricultural production activities. [Conclusion] The prevention and control of heavy metals in the water bodies of the Hanzhong section of the Hanjiang River should focus on Cu pollution, monitor the concentration changes of heavy metals such as Cr and Pb, optimize the layout of mining and smelting enterprises along the river, improve farmland soil to reduce the migration of heavy metals, and protect the water quality safety in this section of the river.
[Objective] Red soils are widely distributed in Yunnan Province, leading to prevalent ecological issues such as soil degradation, runoff erosion, and vegetation deterioration in the region. Under alternate wetting and drying conditions formed by rainfall, high temperature, and evaporation, red soil bodies are prone to structural deformation, shrinkage cracking, surface erosion, and overall instability. This study aims to reveal the mechanism by which glutinous rice gel reconstruction affects the water retention characteristics of red soil under alternate wetting and drying conditions. [Methods] Four gradients of glutinous rice gel concentration levels were designed: 0% (control group), 0.5%, 2.5%, and 5.0%. At each concentration level, two ring cutter samples (separated by filter paper) were prepared, with three replicates for each concentration, resulting in a total of 24 test samples. Ten groups of glutinous rice gel-reconstructed soil samples with different moisture contents were prepared using the gravimetric method, with moisture content gradients evenly distributed from the air-dried state (4.1%) to the saturated state (42.0%). Five equally spaced moisture content gradients were set for each wetting-drying cycle. Two complete cycles of alternate wetting and drying were performed. Matric suction was measured using the filter paper method. By achieving moisture balance exchange between the filter paper and the soil samples, the matric suction of the soil samples was determined based on the standard relationship between the filter paper’s balance moisture content and suction values. Parameter fitting of the soil-water characteristic curve (SWCC) was performed based on the Logistic model. [Results] Alternate wetting and drying significantly influenced soil matric suction. The matric suction of plain soil decreased by 79.43%, while the glutinous rice gel-reconstructed soil exhibited notable protective effects, with the concentration level of 5.0% demonstrating optimal performance and only decreasing by 8.56%. Hysteresis analysis of the SWCC showed that glutinous rice gel effectively suppressed the hysteretic effects caused by alternate wetting and drying. At the concentration level of 5.0%, the hysteresis degrees of the first and second cycles were reduced by 80.76% and 72.42%, respectively, significantly outperforming plain soil (p<0.01). The Logistic model exhibited high fitting accuracy for SWCC (R2>0.99). Parameter analysis indicated that the 2.5% concentration level exhibited optimal water retention performance during the drying phase, while the 5.0% level performed best during the wetting phase. During alternate wetting and drying, the air-entry value and residual value of the glutinous rice gel-reconstructed soil showed regular differences. With increasing cycle numbers, the air-entry value of the sample with 5.0% concentration level decreased by only 36.64% (95% in the control), while the residual value decreased by only 20.24% and 25.43% during drying and wetting, respectively, demonstrating excellent stability. [Conclusions] The incorporation of glutinous rice gel significantly enhances the water retention capacity and matric suction maintenance of red soil, with the 5.0% concentration level demonstrating optimal performance in suppressing suction reduction, followed by 2.5% and 0.5%. Although alternate wetting and drying causes pronounced hysteresis effects in the SWCC of glutinous rice gel-reconstructed soil, higher concentration levels of glutinous rice gel significantly reduce the hysteresis degree and moisture content variation amplitude. The data reveal a significant negative correlation between glutinous rice gel concentration and hysteresis degree (R2=0.92). The 5.0% sample has the maximum hysteresis reduction and is least affected by alternate wetting and drying. The Logistic model can accurately represent the SWCC parameters of glutinous rice gel-reconstructed soil (R2>0.99). Notably, the sample of 2.5% concentration level shows optimal water retention performance during the drying phase, while the 5.0% sample shows the strongest water absorption capacity during the wetting phase, both significantly outperforming the plain soil control group (p<0.01). With increasing numbers of alternate wetting and drying cycles, both the air-entry value and residual value of the soil exhibit decreasing trends. However, the decline in the air-entry value of glutinous rice gel-reconstructed soil is significantly reduced (the 5.0% group decreased by 63% compared to the control group), and the decline rate of residual value tends to stabilize as cycle numbers increase. The residual values of the samples with 5.0% concentration level decrease by 20.24% and 25.43% during drying and wetting phases, respectively, showing optimal water retention stability. Further in-depth research is required on the degradation rate of glutinous rice gel, number of cycles, time variations, and how these affect the properties of red soil and subsequently alter its matric suction.
[Objective] Water and soil loss on cultivated land is characterized by high erosion intensity and poor capacity of soil to retain water, conserve soil, and maintain fertility. Currently, national dynamic monitoring results on water and soil loss cannot be fully applied to the comprehensive management of water and soil loss on cultivated land. Based on existing national dynamic monitoring results on water and soil loss, this study proposes a multi-scale identification method using aggregation analysis to prioritize comprehensive management targets for cultivated land water and soil loss. Priority levels are determined for each treatment unit, providing technical support for efficient and precise evaluation and management planning. [Methods] This study selected Yuexi County in Sichuan Province as the research area. Through spatial overlay analysis of land-use raster data and soil erosion intensity raster data, the data reclassification, regional merging, and removal of small patches were performed to construct contiguous management zones. Depending on water and soil loss characteristics, cultivated land distribution patterns, and patch fragmentation degree, the study extracted cultivated land management targets of varying sizes and calculated their respective erosion grid ratios. A composite evaluation index was then derived by multiplying three graded indices: soil erosion grid ratio, management area level, and average slope level. The comprehensive management priorities were ultimately determined according to the evaluation index values. [Results] Using the proposed method, Yuexi County was classified into five comprehensive management zones for cultivated land water and soil loss, effectively covering the main severely affected cultivated areas. As the priority level increased, the land area, proportion of water and soil loss area, and erosion intensity increased. According to the zoning results of cultivated land in Yuexi County, Zone Ⅰ exhibited mild water and soil loss, with limited impact on the county’s overall loss conditions. Zone Ⅱ showed an increase in water and soil loss, with scattered distribution, suitable for decentralized strategies as a short-term comprehensive management area for cultivated land. Zone Ⅲ comprised large, contiguous areas of cultivated land and was the focus for medium- to long-term soil and water loss comprehensive management. Zone Ⅳ had large areas of high-intensity, concentrated erosion and served as the main area for reducing and mitigating soil and water loss in the county. It was a key area for planning medium- to long-term management of cultivated land. Zone Ⅴ suffered from the most severe water and soil loss, with large area, high proportion of high-intensity loss, and great difficulty in treatment. It should be treated as a priority area for intensive, long-term management efforts. [Conclusion] By comprehensively considering slope, loss area, and erosion ratio and setting appropriate thresholds for decision-making factors, the resulting comprehensive management area can effectively cover severely affected cultivated lands in the county. These zones accurately reflect the spatial distribution patterns of water and soil loss and clarify the priority levels of treatment intensity. To enhance the accuracy and applicability of this study, it is recommended to incorporate additional decision-making factors, including local topography, precipitation patterns, soil properties, and engineering measures. This multidimensional approach will enable more precise identification of representative comprehensive treatment targets, thereby providing a robust scientific basis for regional planning and formulation of optimal remediation strategies.
[Objective] In 2023, influenced by abnormal atmospheric circulation and sea temperature anomalies, the Dianchi Lake Basin, situated in the central Yunnan-Guizhou Plateau, suffered a severe drought. The basin did not enter the rainy season until late June. The annual average temperature, highest daily average temperature, total number of meteorological drought days, and number of extreme drought days all broke historical records, leading to a substantial reduction in river inflow and limited water replenishment of lakes and reservoirs. This study aims to enhance the ability to respond to high-frequency drought events and to guide drought relief efforts under the compounded effects of drought. [Methods] Based on long-term hydrological data series in the basin, this study analyzed the precipitation and runoff conditions in 2023 using GIS-based spatial interpolation and mathematical statistical methods. The drought condition in 2023 was diagnosed using the Standardized Precipitation Index (SPI) and low-flow return periods. [Results] In 2023, the Dianchi Lake Basin experienced a drought event with extensive spatial coverage and long duration, manifesting as a basin-wide moderate-level drought. Nine months of the year had basin-wide droughts of varying degrees, and one month had localized drought. Among them, months with severe drought or above accounted for half of the year. River runoff showed phenomena of low flow during the flood season and an early onset of low flow. From April to July and September to December, control cross-sections experienced low flows with return periods of 100 years or more, causing severe shortages in regional water storage projects and urban-rural water supply and use, thereby profoundly impacting the sustainable utilization of water resources. The analysis indicated that precipitation and water resources in the basin may exhibit a continuous decreasing trend. This drought event was a typical case of the combined effects of “circulation anomalies, underlying surface feedback, and water resource vulnerability.” [Conclusion] This study recommends suggestions integrating intelligent early warning,engineering resilience,and institutional innovation:1) improving the drought prediction, forecasting, and early warning system; 2) accelerating the construction of the Central Yunnan Water Diversion Project and small-scale water source projects; 3) strengthening water resource management and scientific scheduling; 4) advancing research on the utilization of rainwater and floodwater resources; 5) exploring the dynamic control of Dianchi Lake’s water level. The findings not only provide a Chinese solution for drought relief in global karst plateau regions but also offer scientific support for in-depth exploration of the occurrence and development patterns of regional droughts, promotion of ecological protection and restoration, enhancement of drought monitoring and early warning systems, and improvement of response capabilities. This holds significant practical importance for ensuring urban and rural water supply security in the context of frequent droughts.
[Objective] Variations in precipitation are important references for reservoir storage and scheduling. This study aims to reveal the precipitation patterns in the catchment area of the Hedi Reservoir under typhoons with different track types (west-track, middle-track, east-track), establish related forecasting experience, and improve typhoon precipitation forecast services. [Methods] Using typhoon track data, daily precipitation observations from monitoring stations in the catchment area, and MICAPS data, statistical methods including linear trend analysis and Morlet wavelet analysis were used to investigate the variation characteristics of typhoon precipitation and the circulation pattern configurations of typhoon-induced rainstorms affecting the catchment area of Hedi Reservoir. [Results] The results showed that: (1) over the past 32 years, the number of typhoons affecting the catchment area showed an increasing trend of 0.33 events per decade, with a 7-year periodic oscillation. The peak typhoon season occurred from July to September, accounting for 77.2% of annual typhoon impact.(2) Typhoon tracks affecting the catchment area were classified into three types: west-track, middle-track, and east-track. Middle-track type was the most frequent, accounting for 46.8% of the total, followed by west-track type at 44.3%, while east-track type was the least frequent, accounting for 8.9%.(3) There were significant differences in precipitation characteristics among typhoons with different track types. West-track typhoons showed large variations in precipitation amount and intensity, with stronger precipitation in the southern catchment area and frequent localized rainstorms. Middle-track typhoons were characterized by large rainfall amounts, extensive areas of intense precipitation, and relatively prolonged duration, with rainstorms to heavy rainstorms dominating the entire catchment area. For east-track typhoons, rainfall amounts varied greatly across stations, and there was currently no reliable forecasting experience.(4) The typhoon-induced rainstorms in the upstream catchment area of Hedi Reservoir were mainly caused by the combined influence of the western Pacific subtropical high, the southwest monsoon, and cold air. Based on an analysis of historical typhoon circulation patterns, an empirical forecasting method for the circulation patterns of west-track and middle-track typhoon-induced rainstorms was preliminarily developed. [Conclusion] The results of this study indicate that the precipitation in the catchment area of the Hedi Reservoir is closely related to typhoon tracks. Forecasting of typhoon tracks and empirical prediction of their circulation patterns can serve as a reference for accurately forecasting reservoir precipitation. These findings provide important guidance for the rational operation of the Hedi Reservoir, coordinated water storage scheduling, meteorological disaster prevention and mitigation, and the full realization of maximum comprehensive benefits.
[Objective] Reservoir water levels fluctuate periodically every year during the operation period. Existing research has shown that the late-term deformation of rockfill dams is mainly caused by the prolonged water cycle loading. To thoroughly understand the impact of periodic reservoir water level fluctuations on long-term dam deformation, this study combines qualitative and quantitative analyses using nearly 17 years of deformation monitoring data from the Shuibuya concrete-faced rockfill dam (CFRD). [Methods] Qualitative analysis focused on the impact of reservoir water level changes on deformations of the dam interior and its downstream face. Quantitative analysis employed the cross-correlation method to investigate the relationship between water level variation and settlement at the section of maximum dam height. [Results] (1) Late-stage settlement deformation was mainly concentrated in the central upstream and upper downstream areas of the dam body, and the settlement and horizontal displacement increments in the upper downstream converged more slowly. (2) The late-stage deformation of dam body was primarily caused by reservoir water level fluctuations. At most measurement points at different elevations within the dam body, the settlement evolution curves exhibited fluctuations with the same frequency as the water level changes and lagged behind them. (3) The correlation coefficients between the dam body settlement increments and reservoir water levels were calculated, verifying a strong correlation between them. (4) The settlement and horizontal displacement increments on the downstream face of the dam were mainly concentrated at the top of the section of maximum dam height, and the influence of reservoir water level variation increased with elevation. [Conclusion] This study analyzes the deformation patterns of high CFRDs under reservoir water-level variations, and the findings provide valuable insights for the late-stage deformation monitoring and safety control in similar projects.
[Objective] To improve the density of dredged silty soil foundation and eliminate the liquefaction risk, we investigated the reinforcement effectiveness of pneumatic vibratory probe compaction method. The focus is on quantitatively analyzing the improvement in physical and mechanical properties of the treated soil, systematically evaluating the enhancement effects of the pneumatic vibratory probe compaction method, and establishing a scientific effectiveness assessment system, thereby providing a novel technical solution for the treatment of weak coastal foundations. [Methods] Comparative tests involving non-filler vibroflotation method and dynamic compaction with pre-drainage were conducted, supplemented by laboratory experiments and in-situ testing. First, field tests were carried out to evaluate the pneumatic vibratory probe compaction method for reinforcing dredged silty soil foundations, during which key construction parameters were determined through theoretical calculations and trial compaction. The excess pore water pressure during construction was monitored in real time using vibrating wire piezometers. Based on the analysis of the maximum pore pressure ratio, the effective horizontal reinforcement range per point was determined to be 1.15 m. Ultimately, a triangular point arrangement was adopted, with the spacing between vibro-points set at 1.8 m. Moreover, wellpoint dewatering was innovatively employed as an auxiliary measure. [Results] Pneumatic vibratory probe compaction method significantly improved the physical and mechanical properties of the soil: the moisture content decreased from the initial range of 25%-38% to 21.8%-35.5%, a reduction of 5.9%-25.7%, and the void ratio reduced from 0.7-1.07 to 0.63-1.02, a reduction of 6.1%-23.9%. Significant improvements were observed in cone tip resistance, sleeve friction, standard penetration test (SPT) blow counts, and surface wave velocities of the soil layers. Notably, SPT blow counts increased by 60%-260%, static cone penetration (CPT) cone tip resistance rose by 39%-75%, and surface wave velocities showed an increase of 18%. All these indicators met design requirements. More importantly, the treated site was completely free from liquefaction risks, demonstrating a substantial enhancement in seismic performance. Comparison between non-filler vibroflotation method and dynamic compaction with pre-drainage revealed that while the dynamic compaction with pre-drainage performed well in shallow soil reinforcement, its effectiveness was limited for deep layers below 8 m. The non-filler vibroflotation method exhibited good performance in soils with high sand and silt content but showed a significant decline in effectiveness when clay content was elevated. Economic analysis indicated that dynamic compaction had higher construction costs, whereas the pneumatic vibratory probe compaction method and non-filler vibroflotation method had similar costs, demonstrating the former’s notable economic advantage. [Conclusions] The wellpoint dewatering auxiliary measure effectively resolves construction challenges associated with high-moisture-content surface soils, creating favorable conditions for the successful implementation of the pneumatic vibratory probe compaction method. Within the treatment zone, the pneumatic vibratory probe compaction method generates greater excess pore water pressures in the middle-to-lower soil layers. This not only induces premature liquefaction but also significantly improves drainage conditions in silty soil layers, thereby expanding the influence range of single-point vibration and substantially enhancing overall reinforcement effectiveness. Furthermore, this technique offers notable advantages including simple construction procedures, no filler requirement, low cost, high work efficiency, and energy-environmental benefits. These characteristics confer both significant economic and environmental advantages, demonstrating broad application prospects for treating weak coastal foundations.
[Objective] Cohesive non-swelling soil (CNS) covering technology, when applied to the in-situ treatment of expansive soil foundations and slopes, frequently necessitates the modification of the expansive soil with traditional additives like lime to prepare suitable CNS materials. Research on the treatment of expansive soil using hydroxy-aluminum remains limited, and its application as an in-situ CNS material has not yet been reported. This study aims to ascertain the viability of using chemically stabilized soil (CSS) with hydroxy-aluminum solution as a CNS cushion layer material through laboratory experiments. [Methods] A series of basic physical-mechanical, chemical, and microstructural tests were carried out. Changes in particle size distribution, Atterberg limits, and compaction indices of soils were analyzed to evaluate the modification effect of hydroxy-aluminum on expansive soil. Subsequently, the permeability, shear strength, and swelling characteristics of the expansive soil (ES), CSS, and CNS were investigated under varying degrees of compaction (85%, 90%, 95%, 100%). Ion concentration analysis of soils and microstructural analyses (XRD, SEM) were also conducted to assess the overall performance of CSS and validate its potential as a CNS cushion layer material. [Results] (1) Following the addition of the hydroxy-aluminum solution, flocculation and agglomeration occurred between the hydroxy-aluminum and the clay particles of expansive soil. This process resulted in a reduction in the dispersibility and hydrophilicity of expansive soil, leading to denser particle packing. Consequently, the particle size distribution of expansive soil shifted, with an increase in silt content from 31% to approximately 46%, and a decrease in clay content from 65% to 51%, indicating a trend toward silty soil. (2) Plasticity index exhibited a substantial decrease, with a 43.5% reduction from 38.06 to 21.49. This decline resulted in a transformation of the soil classification from high-liquid-limit clay (CH) to low-liquid-limit clay (CL). These changes demonstrated a marked improvement in the basic physical properties of expansive soil. (3) Under varying degrees of compaction, the CSS exhibited substantial improvements in permeability, shear strength, and swelling characteristics compared to expansive soil. The permeability coefficient increased from 10-8 to 10-9 cm/s to the order of 10-7 cm/s, reaching a level comparable to that observed in the CNS. The shear strength parameters were enhanced; notably, at high compaction degree (K=100%), the shear strength of CSS even exceeded that of CNS. The swelling potential of CSS was significantly reduced, with the development of swelling deformation following the same trend as CNS. The swelling percentage decreased from 16%-24% to 8%-15%, representing a reduction of 37.5%-50%, which was slightly higher than CNS but still within the range of non-swelling soil. [Conclusion] Overall, the comprehensive performance of CSS was found to be essentially equivalent to that of CNS. The modification of expansive soil by hydroxy-aluminum solution primarily involved physicochemical reactions, including adsorption, ion exchange, and flocculation-agglomeration. The concentrations of K+, Na+, Ca2+, and Mg2+ of CSS all showed a significant increase. The findings suggest that CSS has a better potential for the inhibition of the swelling behavior of expansive soil. The results demonstrate the feasibility of utilizing CSS as a CNS cushion layer material for expansive soil.
[Objective] Accurate prediction of tunnelling-induced vertical responses in pile foundations remains a critical challenge in urban underground construction. Traditional deterministic analyses of the complex tunnel-soil-pile interactions often assume homogeneous soil properties, neglecting the inherent spatial variability of soil properties. Such simplifications may result in underestimating or misrepresenting pile responses. To bridge this gap, the primary objective of this study is to develop and implement a sophisticated probabilistic model capturing the vertical spatial variability of soil properties. This model aims to facilitate a comprehensive stochastic analysis and provide more realistic and reliable predictions of pile behavior due to adjacent shield tunnel excavation. [Methods] The core deterministic framework employed a well-established two-stage analytical procedure: first, tunnelling-induced free-field ground movements were modeled using the Loganathan-Poulos solution, which accounted for volume loss and tunnel geometry effects on surrounding soils; second, pile foundation responses to these soil displacements were evaluated through Load Transfer Analysis to calculate pile head settlements and axial force distributions along the pile shaft. Undrained shear strength was modeled as a random field to account for the vertical spatial variability. The two-stage deterministic procedure and the vertical random field model for undrained shear strength were integrated within an automated Monte-Carlo simulation framework, which constituted the developed stochastic Two-Stage Analysis model. After a sufficiently large number of iterations, the recorded pile responses were statistically analyzed, yielding the probability distributions, mean values, and standard deviations for the pile head additional settlement and the maximum additional axial force along the pile shaft. [Results] Both the coefficient of variation and the correlation length of the undrained shear strength exerted a significant influence on the statistical moments of the pile responses. An increase in the coefficient of variation generally led to higher mean values of pile head additional settlement and the mean maximum additional axial force. The correlation length caused significant variations in both the mean and, particularly, the standard deviations of pile settlements and axial forces compared to the homogeneous case. The probability of pile head additional settlement exceeding a critical serviceability limit state showed a strong dependence on the vertical spatial variability of soil strength. As the overall variability increased, the computed probability of settlement failure rose significantly. The detrimental impact of soil spatial variability on pile reliability amplified by higher levels of deterministic loading factors. Increased ground deformation caused by larger tunnel volume loss intensified the negative effects of soil variability. In addition, existing structural loads applied to the pile head further magnified the sensitivity of pile responses and the associated failure probability to the underlying soil uncertainty. Essentially, the combined loading conditions made the pile foundation more vulnerable to the adverse consequences of spatially variable soil properties. [Conclusion] (1) The proposed stochastic two-stage model successfully bridges the gap between conventional analytical methods and real-world soil heterogeneity. (2) The developed Monte-Carlo automation program can provide practical guidelines for prioritizing vertical variability characterization in geotechnical investigations and for adopting probabilistic design methods instead of conventional safety factors. (3) The current model neglects horizontal soil variability and construction disturbances. Future work should integrate 3D random fields with machine learning techniques for enhanced prediction.
[Objective] In engineering areas with minor topographic relief, horizontal stress can be approximately used as the stress condition for underground engineering design, and 2D hydraulic fracturing method is generally applicable for in-situ stress testing. However, in deep valley areas with significant topographic relief, planar stress is no longer sufficient to represent the principal stress characteristics of the engineering area. Based on the Dongzhuang Water Conservancy Hub Project, this study aims to reveal the stress distribution patterns of rock mass in deep valley areas. [Methods] In-situ stress testing using hydraulic fracturing method was conducted in boreholes drilled on the riverbed slope and within test adits of the underground powerhouse area. Based on the three-borehole intersection hydraulic fracturing method for in-situ stress testing in the underground powerhouse area, the 3D stress results at the borehole intersections were obtained. A comparison between 2D horizontal stress and 3D spatial stress showed that in mountainous areas affected by valley and slope topography, there was a significant angle between the spatial principal stress and the horizontal principal stress vectors. Therefore, when constructing underground caverns in shallow mountainous areas with valley slope topography, the 3D spatial stress was the true stress condition that needed to be considered, and 3D in-situ stress testing was more representative. Additionally, numerical inversion analysis of the stress field was performed. [Results] The stress magnitude above the valley elevation in the engineering area was significantly influenced by slope topography, with stress contour lines basically distributed along the direction of the slope gradient. In the powerhouse area, the maximum principal stress was primarily governed by self-weight stress. Under the fault zone of the deep valley on the northwestern side, the residual horizontal tectonic compressive stress in the mountainous areas above the riverbed elevation was minimal or had largely been released over geological time. At the riverbed bottom, pronounced stress concentration was observed due to horizontal tectonic compression and the subduction effect from adjacent valley slopes, forming a typical valley “stress concentration zone”. Below the valley elevation, as the rock mass burial depth increased, the stress magnitude increased, with diminishing influence from surface morphology. The stress contours exhibited a horizontal distribution, indicating that the deep stress field was mainly controlled by horizontal tectonic compression. Near the valley, the orientation of the maximum horizontal principal stress tended to be orthogonal to the valley trend. With increasing distance from the valley, the influence of valley topography on in-situ stress weakened, and the orientation of maximum horizontal principal stress gradually deflected toward the measured stress orientation in the powerhouse area. Furthermore, based on the differentiation characteristics of in-situ stress in the valley area of the Dongzhuang Water Conservancy Hub Project, the area could be roughly divided into four zones: stress relaxation zone, stress transition zone, stress concentration zone, and stress stabilization zone. The rock mass thickness for each zone was determined according to the characteristics of stress variation. [Conclusions] This study investigates the abnormal reduction in measured in-situ stress at the bottom of vertical boreholes in the powerhouse area. Based on the dissolution traces observed in drilling cores and borehole videos, along with hydrogeological surveys, it is demonstrated that the long-term groundwater flow connectivity at the riverbed elevation has caused dissolution, forming relatively concentrated dissolution pores and fissures. The presence of these fractures alters the continuity and integrity of the rock mass, providing pathways for in-situ stress release, affecting stress transmission, and further resulting in stress reduction and uneven distribution. Thus, the abnormal reduction in stress magnitude with depth at the bottom of vertical boreholes is reasonably explained.
[Objective] In underwater engineering inspection, the turbid shallow water environment severely hinders the performance of machine vision-based methods for detecting surface defects in underwater structures. To address the challenge of defect detection in turbid water, this study proposes a lightweight three-stage underwater defect detection method that integrates polarization imaging and deep learning techniques. A defect detection model, named PCC-YOLOv7, is developed. [Methods] First, polarization imaging technology was combined with a polarization restoration model to analyze the polarization characteristics of light waves. This approach effectively suppressed scattering interference in turbid water, thereby achieving clear imaging of turbid environments and restoring defect images. Consequently, defect details obscured by scattering particles were reconstructed. Second, the CAA-SRGAN (Coordinate Attention ACON-Super Resolution Generative Adversarial Network) model was introduced. By employing an improved attention mechanism and a generative adversarial network structure, super-resolution processing was performed on the restored images. This yielded high-resolution underwater defect images, providing a high-quality data foundation for subsequent precise detection. Finally, a defect detection model based on CBAM-YOLOv7 was established, where the convolutional block attention module (CBAM) was utilized to enhance the network’s focus on defect features. Leveraging the advanced YOLOv7 object detection framework, common underwater structural defects, including cracks, holes, and spalling can be rapidly and accurately identified. These three sub-models worked collaboratively to form a comprehensive detection system. [Results] For image restoration, the polarization restoration model exhibited superior performance in metrics such as image clarity and color fidelity compared to current restoration methods. The CAA-SRGAN model generated images with notable improvements in detail texture preservation and resolution enhancement. The CBAM-YOLOv7 defect detection model achieved higher accuracy in both defect localization and classification. A comprehensive evaluation of the PCC-YOLOv7 defect detection model revealed an average improvement of 33.5% in mean average precision (mAP0.5, mAP0.75, and mAP0.5-0.95). Compared to existing models, PCC-YOLOv7 significantly enhanced defect detection performance in turbid underwater environments, effectively improving both recognition rate and detection efficiency. [Conclusions] The PCC-YOLOv7 defect detection model innovatively integrates polarization imaging technology with deep learning. Through the collaborative operation of three functionally complementary sub-models, it successfully addresses the challenge of detecting surface defects in underwater structures in turbid water. Compared to existing models, the proposed model demonstrates enhanced adaptability to turbid underwater detection scenarios. It enables stable and efficient detection of surface defects in underwater structures under complex turbid conditions, providing a practical technical solution for the safety assessment and maintenance of underwater structures. Future work may focus on further optimizing the model structure and extending its application to more underwater scenarios.
[Objective] The material composition of high core rockfill dams is complex. Under the influence of hydraulic loading, temperature, and other complex environmental factors during long-term service, the permeability coefficients of these materials inherently exhibit time-varying characteristics, significantly influencing seepage stability and overall dam safety. This study aims to address the limitations of existing research, which predominantly focuses on static parameter inversion or non-time-varying risk assessment, and lacks systematic consideration of the time-varying patterns of material parameters and the influence of long-term operation. [Methods] A time-varying risk analysis method for seepage failure in high core rockfill dams was proposed, integrating data decomposition, finite element simulation, time-varying parameter inversion, and failure risk analysis. First, based on multi-year measured seepage pressure data of the dam, empirical mode decomposition was used to extract the periodic and trend components. Combined with orthogonal experiments and response surface methodology, an inverse surrogate model for the permeability coefficients of the high core rockfill dam and its foundation was constructed. Subsequently, through optimization using a genetic algorithm, this study investigated and revealed the time-varying patterns and characterization functions of permeability coefficients. Finally, based on the time-varying patterns of permeability coefficients and the Monte Carlo method, a time-varying risk analysis model for seepage failure in high core rockfill dams was established to achieve the dynamic risk assessment of seepage failure in the dam structure. [Results] This method was applied to the Pubugou Dam project. The results showed that the relative error of permeability coefficient inversion for both the dam and foundation was less than 2%, with an average relative error of 0.4%. Seepage field simulations based on the inverted parameters showed that the distribution of seepage pressure inside the dam followed the rising and falling trend of the reservoir water level and was consistent with the patterns observed in the measured seepage pressure data. This conformed to the typical seepage field distribution patterns of high core rockfill dams, indicating a high level of inversion accuracy. Furthermore, the permeability coefficients of both the core wall and the overburden layer showed time-varying patterns of gradual increase and stabilization. Reliability analysis of seepage failure in the dam and its foundation indicated that the reliability indicator (β) of the dam consistently exceeded the design target value during the operational period, suggesting that the overall risk of seepage failure was low. Additionally, the reliability indicator for seepage failure in the dam and its foundation exhibited periodic fluctuations with changes in the reservoir water level, showing a generally negative correlation between the reliability indicator and reservoir water levels and a positive correlation between failure probabilities and water levels. This was generally consistent with the seepage characteristics and patterns of dam structures under different water level conditions, validating the applicability of the proposed time-varying risk analysis model. The results confirmed that the reliability indicator for seepage failure of the Pubugou Dam complied with regulatory requirements. [Conclusions] The method developed in this study integrates time-varying parameter inversion, modeling of time-varying patterns, failure path search, surrogate model construction, and time-varying risk analysis. By dynamically identifying and updating time-varying parameters in real time, it enables accurate simulation of seepage failure processes and full lifecycle monitoring of risk evolution, thereby enhancing the timeliness and accuracy of safety risk assessments for high dam structures.
[Objective] With the implementation of China’s dual-carbon strategy, pumped storage has become increasingly important in the new-type power system dominated by renewable energy resources. As the operating intensity of pumped storage units continues to increase, vibration problems of pumped storage powerhouses have become increasingly common. It is necessary to summarize solutions to vibration problems in operating pumped storage power stations and units to guide the design of future stations. [Methods] This study presented the identification of vibration sources and solutions to vibration issues of pumped storage power stations in Zhanghewan, Heimifeng, and Guangzhou. Two widely used structural design schemes for pumped storage powerhouses—thick-plate continuous wall structure and plate-girder frame structure—were presented, with a discussion of their advantages and disadvantages. Based on the actual cases, the layout of vibration measurement points for both the powerhouse and the unit was provided. Test methods and evaluation indicators were established for powerhouse vibration. [Results] Three typical methods for alleviating vibration in the powerhouse and pumped storage unit were proposed: controlling the energy generated by hydraulic excitation sources, staggering the frequencies between stationary parts and hydraulic excitation sources, improving the local or overall stiffness of structures. For structure stiffness and vibration resistance, the thick-plate continuous wall structure and plate-girder frame structure showed no significant difference. For the measurement and calculation of powerhouse vibration, more attentions should be paid to individual structural components to prevent local resonance with hydraulic excitation sources. [Conclusion] Both the thick-plate continuous wall structure and plate-girder frame structure can be widely used for pumped storage power stations, depending on specific engineering requirements. The natural frequencies of overall and local powerhouse structures should maintain a frequency deviation of 20% from hydraulic excitation source frequencies. If the vibration velocity is used as an evaluation indicator, the maximum vibration values should be less than 10 mm/s on the powerhouse floor and 5 mm/s in the pit. This study provides important guidance for improving the structural design of pumped storage power stations in China.
[Objective] This study focuses on the issue of cracking in the support structures of high-temperature water diversion tunnels during the operation period caused by excessive tensile stress. An active thermal control strategy involving the application of thermal insulation coatings with specific thicknesses before water flow in the tunnel is proposed and systematically quantified. This study evaluates the regulatory effect of this strategy on the temperature and stress fields throughout the life cycle of the tunnel (from construction to operation) and its role in improving crack resistance safety. [Methods] Based on a three-dimensional thermo-mechanical coupled finite element method, a typical high-temperature water diversion tunnel was used as the engineering background. The temperature evolution and stress response of the structure under different thermal insulation coating thicknesses were precisely simulated. [Results] The thermal insulation coating significantly improved the temperature gradient of the secondary lining. As the coating thickness increased, the temperature difference between the inner and outer sides notably decreased. The application of thermal insulation coating before water flow in the tunnel effectively suppressed the temperature difference between the inner and outer sides of the secondary lining and the resulting tensile stresses. The coating thickness was positively correlated with the reduction in tensile stress, leading to a corresponding decrease in the area of zones that did not meet crack resistance safety criteria. In particular, when the coating thickness was 2 mm, the peak tensile stresses at all key locations of the secondary lining were below the ultimate tensile strength of the material. Except for localized high-stress zones, the crack resistance safety factor in the majority of the zones remained stable above 1.6, significantly outperforming the no-coating or thin-coating schemes. [Conclusion] Pre-applying a thermal insulation coating of appropriate thickness (such as 2 mm) before water flow in the tunnel is a highly efficient and innovative thermal control and cracking prevention strategy. This source-intervention approach significantly reduces the tensile stresses induced by temperature loads, fundamentally enhancing the structural safety and durability of high-temperature tunnels during long-term operation. The research findings provide direct quantitative design guidance and key technical support for similar engineering projects.
[Objective] With increasing water resource development and growing ecological demands in the Hanjiang River Basin, conflicts between intra-basin water consumption and inter-basin water transfer, as well as between comprehensive water utilization and ecological water allocation, have become increasingly prominent. It is necessary to strengthen water allocation capacity through scientific methods, coupled with coordinated strategies for riverine-lacustrine habitat restoration and ecosystem health maintenance. [Methods] To address the coordinated requirements of water supply, power generation, and ecological benefits, a multi-objective optimized scheduling model for the Danjiangkou Reservoir was established, with the objectives of maximizing water transfer volume to the North, annual power generation, and ecological flow guarantee rate. The NSGA-III algorithm was innovatively improved by introducing a differential mutation operator and an adaptive crossover strategy, thereby enhancing the solution efficiency of the multi-objective optimization model. Additionally, a river hydrological health assessment method was incorporated to provide new insights for maintaining the ecological stability of the reservoir river section and the middle-lower reaches of the Hanjiang River. [Results] The optimization results showed that the ecologically optimized scheme significantly improved the ecological flow guarantee rate, with increases of 100%, 46.65%, and 88.89% in wet, normal, and dry years respectively. The optimization effects were significant, maximizing ecological benefits while strengthening water allocation. The river hydrological health assessment of the ecologically optimized scheme revealed that under low-inflow conditions, the optimized scheme effectively promoted overall river hydrological health. [Conclusion] The optimized scheme plays a positive role in ensuring the water transfer volume to the North, improving the ecological environment of the middle and lower reaches, and strengthening water resource allocation. Under reduced inflow conditions, compared to the conventional scheme, the optimized approach substantially improves comprehensive utilization efficiency and reduces water wastage. While pursuing ecological benefits, it alleviates the competition between ecological, water supply, and power generation demands. Furthermore, the river hydrological health assessment of the ecologically optimized scheme demonstrates that under low-inflow conditions, the optimized approach helps enhance overall river hydrological health, thereby promoting ecological stability in the downstream of the Danjiangkou Reservoir during dry periods. This study provides new insights for maintaining the ecological stability of the reservoir river section and the middle-lower reaches of the Hanjiang River.
[Objective] Short-term optimal scheduling of cascade reservoirs is complicated by hydraulic connections among power stations and environmental factors, and most studies neglect the risk of deviating from normal operations. Therefore, this paper proposes a plan completion rate indicator that comprehensively measures deviation and scheduling target satisfaction using the Feature Similarity Index (FSI), and constructs a short-term multi-objective optimization model aiming to maximize cascade power generation and plan completion rate. [Methods] For the short-term multi-objective joint optimization scheduling of the lower-Jinsha River cascade, K-means clustering of historical plant data was first conducted. Silhouette coefficient (SC) and Davies-Bouldin index (DBI) were used to select the optimal number of clusters for each station on a monthly basis. Typical generation patterns were then extracted based on these optimal clusters to provide a data foundation for the subsequent scheduling model. Further, a multi-objective model maximising power generation and plan-completion rate, using the Feature Similarity Index (FSI) to comprehensively evaluate deviation and the degree of scheduling target fulfillment, subject to water balance, water level, discharge and output constraints, was built and solved by NSGA-II (using a water-level corridor to handle hard constraints). The final scheme was selected using the entropy weight method and the VIKOR multi-criteria compromise ranking method. [Results] In the case study, Pareto solutions showed a clear trade-off between power generation (921.52-922.13 million kW·h, range 0.61 million kW·h) and FSI (0.831 6-0.872 6, range 0.041) with evenly distributed results. Entropy weighting assigned weights of 0.513 2 to generation and 0.486 8 to FSI. The VIKOR-selected compromise scheme (closeness coefficient 0.002 2) yielded 921.98 million kW·h (7.4% above normal 857.2 million kW·h) and an FSI of 0.861 2, occupying 74.63% and 72.03% of their respective ranges. Except for Xiluodu, the outputs variation trend of Xiangjiaba, Three Gorges, and Gezhouba plants generally aligned with the typical generation patterns. [Conclusion] The results show that the model effectively balances power benefits with output process deviation and quantifies generation improvements under varying plan completion rates. By scientifically selecting optimal cascade scheduling schemes, it offers reliable references for operators of the cascade reservoirs in the lower-Jinsha River-Three Gorges region and supporting medium-/long-term schedule adjustments as well as the formulation of reservation-period plans.
[Objective] Optimizing the scheduling of flood control water levels in reservoirs has become a key technical approach to cope with extreme flood and drought disasters. Focusing on the challenges of unclear allocation efficiency of reservoir capacity and hierarchical scheduling of water levels for flood control in the cascade reservoirs of the Yalong River Basin, we established a multi-objective scheduling model for flood control water levels of cascade reservoirs, aiming to achieve coordinated scheduling of both flood control and beneficial utilization goals. [Methods] The study focused on three key control reservoirs—Lianghekou, Jinping I, and Ertan—in the Yalong River Basin, and used flood hydrographs derived from typical flood events in 1965 and 2000 under different design frequencies (P=1%, 0.5%, 0.2%, and 0.1%) as input data. The objective functions of the proposed model include: minimizing the peak discharge at the outlet cross-section, minimizing the water level at the end of the scheduling period, minimizing the highest water level during the scheduling period, and minimizing the total utilized flood control reservoir capacity, while considering constraints such as water balance, discharge capacity, and upper and lower water level limits. The model was solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to generate the Pareto solution set, and the entropy-weighted VIKOR method (EMW-VIKOR) was used to rank and select the optimal scheduling schemes. [Results] (1) Significant trade-off among the objectives existed. The peak flood discharge at the outlet cross-section of the river basin showed a clear competitive relationship with the water level recovery rate of upstream reservoirs at the end of the scheduling period, the maximum water level during the scheduling period, and the total utilized flood control reservoir capacity. Analysis of flood control reservoir capacity allocation indicated that as the flood magnitude increased, the allocated flood control capacity of Jinping I increased, the total utilized flood control capacity of cascade reservoirs decreased, and the peak discharge affecting downstream protected areas decreased. (2) The optimal flood control water level schemes were obtained after comparison and selection. For Lianghekou Reservoir, the flood control water level could be raised from 2 845.9 m to 2 848.44-2 850.88 m, an increase of 2.5-5 m. For Jinping I Reservoir, from 1 859.06 m to 1 859.76-1 860.83 m, an increase of 0.7-1.8 m. The flood control water level of Ertan Reservoir could be raised from 1 190 m to 1 192.13-1 192.96 m, an increase of 2-3 m. (3) The optimized scheduling schemes demonstrated significant comprehensive benefits. Compared with conventional scheduling schemes, the error in reservoir water level recovery rate at the end of the scheduling period was less than 0.5% under different design frequencies. The highest water level indicator approached 1 (e.g., 0.997 9 at P=0.1%) without exceeding flood control upper limits. The utilized flood control reservoir capacity was reduced by 300 million m3 or more, including a reduction of 566 million m3 under the design frequency of P=1%. Taking the flood event on July 29, 2024 as an example, the optimal scheme increased power generation by 255 million kW·h (an improvement rate of 9.7%) compared with the actual scheduling, while achieving a lower peak flood control water level and a water level recovery rate of 100% at the end of the flood season, demonstrating significant improvements in both flood control and beneficial utilization. [Conclusion] This study proposes a multi-objective optimization model for flood control water level scheduling in cascade reservoirs, reveals the allocation efficiency of flood control reservoir capacity, and provides a multi-objective coordinated scheduling scheme for flood control water levels of cascade reservoirs. The findings provide technical support for floodwater resource scheduling of cascade reservoirs in the Yalong River Basin and enhance the utilization level of water resources in the river basin.
