[Objective] Focusing on the Yingwen River Basin in Shandong Province, this study aims to explore the extraction, division, naming methods for small watersheds in mixed terrains, and to analyze spatial distribution characteristics of small watershed areas and river network densities. [Methods] This study utilized high-precision SRTM-DEM data, combined with hydrological analysis modules, to extract micro-watersheds, river networks, and watershed boundaries. The optimal catchment threshold was determined using the river network density method. Micro-watersheds were merged into small watershed units based on natural catchment relationships, and named according to Specification SL 653—2013. In complex terrain areas, local corrections were made by referencing high-resolution remote sensing images and field survey results to ensure the accuracy of the division. Meanwhile, the main stream, first-order tributaries, and second-order tributaries of the Yingwen River Basin were extracted, and the characteristics such as the area of small watersheds and the density of river networks were statistically analyzed. [Results](1) This study successfully extracted 1 main stream (the main stream of Yingwen River), 22 first-order tributaries, 48 second-order tributaries, and 1 large reservoir, establishing a complete water system network. (2) A total of 28 small watersheds were merged. Small watershed areas in upstream mountains were generally smaller, while those in downstream hilly plains were relatively larger. This was mainly caused by terrain limitations combined with human activities. (3) All 28 small watersheds were named based on the proposed naming process, providing strong support for watershed management and water resource protection. (4) The river network density in Yingwen River Basin exceeded 0.2 km/km2, indicating abundant water system resources. Areas with river network densities of 0.4-0.6 km/km2 accounted for 60.71% of the total area, mainly concentrated in the middle and lower reaches. Areas with densities of 0.6-0.8 km/km2 accounted for 28.57%, distributed in the upper, middle, and lower reaches. [Conclusion] (1) The analytical framework for division, naming, and spatial distribution characteristics of small watersheds in mixed terrains proposed in this paper provides scientific methods and practical cases for similar studies. (2) Complete-type small watersheds are dominant, indicating relatively intact water systems with limited human disturbance. The spatial distribution characteristics of small watershed areas and river network densities reveal the combined influence of terrains and human activities on water system development. (3) The number of first-order tributaries in the Yingwen River Basin exhibits a significant increasing trend from upstream to downstream, reflecting the complexity of river network systems in middle and lower reaches and the promoting effect of human activities on water system development. The distribution characteristics of the length of tributaries per unit area and the density of river networks further reveal the abundance and spatial differences of water system resources within the basin.
[Objective] The "Three Lines and One Permit" (TLOP) eco-environmental zoning management system plays a crucial role in the development of ecological civilization in China. However, its in-depth integration with Environmental Impact Assessment (EIA) for integrated river basin planning remains underdeveloped. To address the prominent conflict between ecological conservation and development in strategic EIA of river basin planning, this study proposes a TLOP-based EIA design framework to ensure the implementation of zoning management requirements. [Methods] A comprehensive EIA framework integrating “planning analysis, environmental assessment, and admittance list” was established. TLOP-based formulation methods for river basins were proposed, including four-category ecological zoning, quantifiable environmental quality baselines, and dynamic control of resource utilization ceilings, which were validated through a case study of the Ganjiang River Basin. [Results] In Ganjiang River Basin, priority conservation waters spanning 200.46 km and key conservation waters covering 592.99 km were delineated. 36 cross-sections for water quality monitoring were established with a Chemical Oxygen Demand (COD) emission limit set at 201 800 t/a. Five conflicting projects, including the Maodian Cascade, were rejected. The ecological flow management was optimized to ensure that the total planned water use (12.94 billion m3) did not exceed the upper limit indicator. [Conclusion] The study achieves innovative dynamic coupling between TLOP and strategic EIA. The developed eco-environmental admittance list for river basins provides precise control of development intensity, offering a replicable paradigm for cross-scale environmental management and facilitating the coordination between high-quality basin development and ecological conservation.
Sediment exchange is one of the key issues in the evolution of riverbed erosion and deposition, and its study holds significant importance for river management and engineering practices. This study systematically reviews domestic and international research progress over the past three decades, focusing on the mechanisms of coarse and fine sediment exchange near the riverbed from four aspects: theoretical models, mathematical models, experimental methods, and field data analysis. The results demonstrate that existing theoretical models (e.g., upward flux formulas based on turbulent bursting, energy balance, and diffusion theories) largely depend on empirical assumptions, lack universally applicable mechanism descriptions, and face limitations due to insufficient field data validation. Although mathematical models describing three-state transitions among suspended load, bedload, and bed material have gradually incorporated probabilistic methods such as Markov chains, they still face challenges in accurately representing sediment exchange process under non-uniform flow conditions. Experimental studies reveal that medium-diameter sediments exhibit higher upward flux due to turbulent bursting and exposure effects. Moreover, formulas for exchange layer thickness dominated by sand wave migration require modifications to account for the influence of resistance transitions in sandy rivers. This study proposes three innovative future directions: (1) integrating prototype observation data to establish unified theoretical formulas for sediment exchange; (2) developing high-precision observation technologies to overcome the bottleneck in dynamically capturing random sediment collision processes; and (3) combining machine learning with physical models to build predictive systems for sediment state transitions. This review provides systematic references for advancing the understanding of sediment exchange mechanisms and optimizing engineering practices.
[Objective] Focusing on the composite-polluted sediments of Ya’er Lake in the Yangtze River Basin, this study aims to address the lack of control indicators for persistent organic pollutants (POPs) in environmental dredging projects. [Methods] A systematic analysis was conducted on the distribution characteristics and ecological risks of three typical pollutants: dioxins, methylmercury, and short-chain chlorinated paraffins (SCCPs). Based on the functional zoning of the lake, differentiated control indicators were proposed. The research methodology integrated comparative analysis of domestic and international standards (including China’s GB 36600—2018, Beijing’s DB11T 811—2011, and standards from Germany and Netherlands), analysis of pollutant migration and transformation mechanisms, and ecological risk assessment models. [Results]The concentration distributions of POPs in Ya’er Lake sediments were measured (dioxins: 1-50 ng/kg, methylmercury: 2-8 342 ng/g, SCCPs: 300-2 000 ng/g). Combined with the co-distribution patterns of heavy metal pollution, the response relationship between pollutant concentrations and lake functions was established. The results showed that control indicators for dioxins should be strictly graded according to lake functions: 10 ng/kg for lakes of landscape and storage functions (aligned with China’s Class I construction land standards), 5 ng/kg for lakes used for agricultural irrigation (referencing German agricultural land standards), and 1 ng/kg for lakes used for fishery purposes (based on background values and Dutch standards). For methylmercury control, the limitations of existing total mercury standards needed to be overcome. It was proposed that when the surface sediment methylmercury concentrations exceeded 5 ng/g, fishery activities should be restricted, with dry excavation identified as the preferred dredging method to minimize secondary pollution risks. For SCCPs control, a threshold of 900 ng/g was first proposed for non-fishery lakes (derived from ecological risk thresholds), while lakes used for fishery purposes required dynamic adjustments based on surrounding agricultural land data. The research demonstrated three breakthroughs: (1) it established for the first time China’s control indicator system for POPs in lake sediments, filling technical gaps in standards like GB 36600—2018 for dredging projects. (2) It revealed a high spatial correlation (R2>0.85) between POPs and heavy metal pollution in Ya’er Lake, proving that dredging according to existing heavy metal standards could simultaneously control POPs risks, thereby significantly reducing remediation costs. (3) It proposed a “function-pollutant-process” integrated control theory, offering a new paradigm for composite pollution remediation. [Conclusion] The conclusions indicate that differentiated control indicators can balance remediation costs and ecological safety. Dioxin standards for fishery water use must be an order of magnitude stricter than current soil standards, methylmercury risk control should be decoupled from total mercury metrics, and SCCPs thresholds must account for water solubility. The study provides critical scientific basis for the revision of standards such as the Technical Specifications for Environmental Dredging of Polluted Lake Sediments, and its methodology can be extended to remediation practices for other composite-polluted lakes globally.
[Objective] Riverine ecological flow quantification is essential for maintaining riverine ecological health. Traditional methods often overlook the joint risks of hydrological and ecological factors and tend to rely on single-scenario calculations. This study aims to establish a joint risk model based on Copula functions and Bayesian theory to quantify the interdependence between hydrological (flow) and ecological (algal density) factors in the middle and lower reaches of Hanjiang River, thereby achieving scientific quantification of ecological flow under multiple scenarios and providing a basis for early warning and regulation of algal bloom risks in rivers. [Methods] Using flow data from Xiantao station and algal density data from Yuekou cross-section during the 2018 algal bloom outbreak in Hanjiang River,this study first determined the marginal distributions of flow and algal density using the Kolmogorov-Smirnov (K-S) test and Akaike Information Criterion (AIC). The optimal Copula functions were then selected using maximum likelihood estimation and goodness-of-fit test. Finally, a joint distribution model of flow and algal density was established, and the Bayesian conditional probability formula was applied to analyze the probability of algal density exceeding the threshold of algal bloom occurrence under different flow scenarios. The results from Copula functions were compared with those from the Tennant method and Hydrological Inflection-Point (HIP) analysis for validation. [Results] (1) The joint distribution model based on Gaussian Copula function passed the K-S test and effectively captured the significant negative dependence structure between flow and algal density.(2) During the 2018 algal bloom outbreak in Hanjiang River, when the flow exceeded 728.00 m3/s and 1 096.30 m3/s, there was over an 80% probability that algal density would exceed 2 561.10×104 cells/L and 902.93×104 cells/L, respectively. (3) The hydrological inflection point method calculated the initial flow of algal bloom with an error within 100 m3/s, demonstrating higher accuracy than the Tennant method. However, both methods underestimated the overall risk due to their neglect of variable dependency. Through bivariate analysis, the Copula model revealed risk details that traditional methods failed to capture. [Conclusions] (1) The joint risk model based on Copula functions can quantitatively capture the complex dependency between hydrological and ecological factors, overcoming limitations of traditional methods that depend on long-term data and neglect multi-factor interactions. It provides an efficient tool for analyzing ecological flow during a single algal bloom outbreak.(2) The multi-scenario conditional probability analysis demonstrates that risk probabilities of algal density differed significantly across different flow ranges, offering refined flow thresholds for reservoir operations and bloom prevention.(3) In complex hydro-ecological systems, it is necessary to integrate multi-factor models like Copula to avoid risk underestimation. This study provides a new method for multi-factor joint risk evaluation and ecological flow quantification in rivers. Future research can further incorporate multiple variables such as water quality and temperature to establish more complex Copula models, improving prediction accuracy and scenario simulation capabilities.
[Objective] Rainfall and runoff are two important hydrological variables in river basins, exhibiting the characteristic of random distribution. In-depth analysis of the relationship between rainfall and runoff holds significant importance for watershed flood risk management, water resource scheduling, and hydraulic engineering planning and design. [Methods] This study utilized the advantages of Copula functions in describing dependence relationships among random variables. First, a non-parametric kernel density estimation method was introduced, and four types of kernel density functions were used to characterize the marginal distributions of rainfall and runoff variables in the Fuchun River Basin. Subsequently, a bivariate Copula function was employed to establish a joint distribution model. Simulation performance for both marginal and joint distributions was validated using root mean square error (RMSE) and Euclidean distance. [Results] (1) By comparing the RMSEs between the estimated results using four kernel density functions (Gaussian, Uniform, Triangle, Epanechnikov) and the empirical frequencies of rainfall and runoff in the river basin, the Gaussian was found to have the smallest errors. The Gaussian was selected to estimate the marginal distributions of hydrological variables in the Fuchun River Basin, demonstrating higher simulation accuracy without relying on any distribution assumption.(2) By estimating the Kendall and Spearman rank correlation coefficients of the bivariate functions of Gaussian-Copula, t-Copula, Clayton-Copula, Frank-Copula, and Gumbel-Copula, and comparing them with the Kendall and Spearman rank correlation coefficients of the original observed data, it was found that Gaussian-Copula and Gumbel-Copula were closer to the observed data.(3) By calculating the Euclidean distance, the fitting performance of the Copula functions was evaluated. The Gumbel-Copula function was further selected as the optimal Copula function to describe the dependence structure between rainfall and runoff in the river basin. It revealed that the rainfall and runoff variables in the upper tail of the joint distribution were highly sensitive to changes, indicating strong correlation between annual rainfall and runoff extreme values in the river basin.(4) Further calculation of the upper tail correlation coefficient yielded a value of 0.758 3, indicating a 75.83% probability of both the annual rainfall and annual runoff reaching extreme values simultaneously. When an extreme value of rainfall occurs in a specific year in the river basin, runoff could be estimated based on the dependence relationship between rainfall and runoff in joint distribution established in this study. This provided a reference for flood risk management. [Conclusion] The Gaussian kernel function demonstrates excellent simulation performance for the marginal distributions of rainfall and runoff variables in the Fuchun River Basin, and the Gumbel-Copula function shows high goodness-of-fit for the joint distribution of rainfall and runoff. The findings of this study offer substantial implications for flood risk management and water resource scheduling in river basins, and provide a theoretical foundation for further research on rainfall-runoff stochastic simulation using Copula functions in the Fuchun River Basin. Additionally, they offer practical value for the calculation and analysis of hydrological variables and for the planning and design of hydraulic engineering in river basins.
[Objective] Following the construction of pumped-storage hydropower plant upstream of conventional hydropower plant, its operation alters the original natural inflow process, causing increased frequency of water level fluctuations and intraday flow reversal regulation, thereby affecting the scheduling processes of the downstream conventional hydropower plants. Such effects are reflected not only in the water level regulation of the downstream conventional hydropower plants, but also in power generation output, operation stability, and economic benefits. A comprehensive analysis of the systematic effect of the operation of the pumped-storage hydropower plants on the downstream conventional hydropower plants holds significant practical value for scientifically developing scheduling strategies for regional power stations and improving overall operational efficiency.[Methods] To systematically and quantitatively analyze this effect, this study proposed a water consumption rate-head curve fitting method based on a multi-layer perceptron (MLP). By integrating this method with the local grid’s time-of-use electricity pricing policy, a power generation scheduling model for conventional hydropower plants was established. Subsequently, the variations in different economic operation indicators of conventional hydropower plants were analyzed under different scheduling modes of pumped-storage hydropower plants.[Results] When the existing scheduling modes of conventional hydropower plants remained unchanged, different scheduling modes of pumped-storage hydropower plants (“dual pumping and dual generation” and “single pumping and dual generation”) resulted in a decline of approximately 0.2 m in the operating water level of downstream conventional hydropower plants. Additionally, the water level regulation process was significantly altered, thereby affecting the generation heads during different periods. Under the “dual-pumping and dual-generation” scheduling mode, the annual power generation decreased by an average of about 6.667 million kW·h, accounting for 0.65% of the multi-year average. The annual power generation benefit decreased by approximately 9.667 million yuan, representing 2.02% of its multi-year average benefit. This was because the pumped-storage hydropower plant occupied part of the conventional hydropower plant’s reservoir storage capacity, lowering the conventional plant’s total generation head, increasing the unit water consumption rate, and reducing the composite output coefficient. Ultimately, the total power generation was decreased. Statistical results indicated that, under the “single-pumping and dual-generation” scheduling mode, the annual power generation of conventional hydropower plants reduced by an average of about 5 million kW·h (0.49% of its multi-year average), and the annual generation benefit declined by about 10.667 million yuan (2.23% of its multi-year average).[Conclusion] Further analysis shows that the operation of the pumped-storage hydropower plants has a pronounced “peak-valley mismatch” effect on downstream conventional hydropower plants: the operation of upstream pumped-storage hydropower plants reduces the maximum operating water level at downstream conventional hydropower plants, decreases the generation head during peak periods, increases available water flow during off-peak periods, and reduces overall water utilization efficiency. Consequently, conventional plants experience reduced power generation during peak periods, increased generation during off-peak periods, and an overall decline in total power generation. Although power generation during off-peak periods increases, the significant differences in electricity prices between the two periods result in insufficient off-peak revenue gains to compensate the losses during peak periods, leading to reduced total annual generation benefit. In summary, this study provides valuable insights for investigating the effects of pumped-storage hydropower plants on downstream conventional hydropower plants and for their planning and construction.
[Objective] This study aims to investigate the hydrological regime alteration in rivers in the soil erosion region of the Loess Plateau under the combined influence of climate change and human activities.[Methods]Using daily runoff data, this study conducted a comprehensive evaluation of the degree of hydrological regime alteration in the basin using the Indicators of Hydrologic Alteration-Range of Variability Approach (IHA-RVA). [Results] Climate warming and soil-water conservation measures jointly led to a significant decrease in the annual average runoff in the Zuli River Basin, with an abrupt change occurring around 1995.Following the abrupt change of runoff, both monthly average flow and related extreme flow indicators exhibited a trend of uniform intra-annual distribution. The degree of change in extreme hydrological indicators was greater than that in monthly average flow indicators,with the change in low-flow duration reaching up to 95% and the change in monthly average flow in November being only 1%.The occurrence time of annual minimum flows advanced significantly,whereas the occurrence time of maximum flows was delayed. After the hydrological abrupt change,both the frequency and duration of high and low flows at the Jingyuan Station decreased significantly.The Zuli River Basin experienced more frequent flow changes,while the amplitude of these changes gradually diminished. After the abrupt change of runoff in the Zuli River Basin, the overall hydrological alteration degree was 48%, which was classified as moderate alteration. [Conclusions] Human activities, primarily driven by soil-water conservation measures, strongly influence the hydrological regime alteration in the Zuli River Basin. Following the abrupt change of runoff, a notable decrease in basin runoff is observed, accompanied by a trend towards more uniform intra-annual distribution. This study provides methodological frameworks and theoretical foundations for ecological conservation and water resource management in arid, soil erosion regions.
[Objective] As an invasive fouling organism, Limnoperna fortunei causes increasingly severe damage to water conservancy projects. To develop new prevention and control methods, this study aims to explore the effects of different light conditions on the behaviors of Limnoperna fortunei. [Methods] The highly active Limnoperna fortunei of different shell lengths were collected from field, acclimated, and then placed in experimental porcelain dishes partially covered with shading plates to create shaded areas. At the beginning of the experiment, the Limnoperna fortunei were exposed to light, and the environmental conditions of different light intensities and different wavelengths of light were established. Four behavioral parameters—shell opening, adhesion, migration, and light avoidance—were used to characterize their responses to light stress, in order to investigate the effects of different light conditions on their behavioral characteristics. [Results] The results of shell opening and adhesion behaviors of Limnoperna fortunei under different light intensities showed that with increasing light intensity, shell opening frequency and material exchange decreased. Strong light inhibited the secretion of byssus and the adhesion behavior of Limnoperna fortunei to a certain extent. Different light colors varied in their effects on byssal adhesion, with white, purple, and red light showing the strongest effects. Specifically, red light at 40 000 lux had the most significant inhibitory effect on byssal adhesion. The results of migration and light avoidance behaviors of Limnoperna fortunei under different light intensities showed that as light intensity increased, migration distance and light avoidance tendency first increased and then decreased. Within the light intensity range of 10 000-20 000 lux, migration distance and light avoidance tendency peaked with increasing light intensity, but reached their minimum at 40 000 lux. The migration distance and light avoidance tendency of Limnoperna fortunei showed similar patterns under different wavelengths of light. Limnoperna fortunei with shell length of 5-10 mm were more affected by light stress and showed higher light avoidance tendency, while those measuring 10-30 mm exhibited greater light tolerance. [Conclusion] In the prevention and control of Limnoperna fortunei, strong light with a light intensity above 40 000 lux can be applied to create unfavorable conditions and reduce their activity. White, purple, and red light with a light intensity of more than 40 000 lux will reduce or affect their adhesion behavior, while light within the range of 10 000-20 000 lux is more effective for expelling Limnoperna fortunei. Although the practical application will be limited by available space, light attenuation, and other factors, light may serve as a simple, fast, effective, low-cost, and environmentally-friendly control method for Limnoperna fortunei.
[Objective] This study focuses on typical water bodies (lakes, rivers inside the polder area, and rivers outside the polder area) in the pilot zone of the Yangtze River Delta, aiming to: (1) analyze the spatiotemporal differentiation characteristics of water transparency (Secchi Depth,SD) in the three typical water bodies; (2) identify the key drivers of SD through correlation and regression models; (3) propose SD improvement thresholds based on the light compensation requirements of submerged vegetation restoration, providing scientific evidence for precise water quality management in plain river networks. [Methods] The study was based on field monitoring data from April to December 2023, focusing on water transparency and other water quality indicators in the Pilot Zone. The analysis combined trends in monthly variations of suspended solids (SS), total phosphorus (TP), chlorophyll-a (Chl-a), and turbidity to explore the spatiotemporal distribution and variation characteristics of SD. Correlation analysis and curve fitting models of SD with turbidity, SS, and TP were employed to quantify the driving mechanisms of SD. Based on the survival needs of local nearshore submerged vegetation, SD thresholds and strongly related water quality improvement targets were established. [Results] (1) River channels within embankments exhibited the highest average SD (68.75 cm), but fluctuated significantly due to rainfall disturbances. The seasonal difference in lake SD was significant (average 61.17 cm), with peak values in winter (80.14 cm) and minimum values in summer (48.00 cm). River channels outside embankments had the lowest SD (45.08 cm) due to strong hydrodynamic disturbances from navigation. Spatially, SD exceeded 70 cm in the southeast of Xitang Town and Lili Town, while SD was below 50 cm in Yuandang Lake, the northeast of Jinze Town, and Taipu River due to aquaculture pollution, construction runoff, and resuspension of bottom sediment. (2) SS concentration was the primary correlated indicator of SD (R=-0.65 to -0.79). The negative correlation between TP and SD was particularly significant in lake water (R=-0.71), and the C3 component (humic-like substances) of dissolved organic matter (DOM) shared a common origin with TP (R=0.64), indicating that TP in lake water mainly originated from soil erosion and surface runoff input. In river channels within embankments, there was no significant correlation between Chl-a and SD (R=-0.14), and Chl-a exhibited the lowest concentration (4.45 μg/L), attributed to the algae-suppressing effect of dense submerged plant growth. (3) SD in channels within embankments was significantly affected by heavy rainfall (73.90 mm in June), with a 20%-40% decrease, while SS (↑60 mg/L) and TP (↑0.12 mg/L) levels significantly increased. However, weak rainfall (≤46.93 mm) had a relatively insignificant effect on water transparency. (4) To maintain local submerged vegetation in the pilot zone, SD should be maintained above 59.14-83.06 cm (calculated based on light compensation depth), corresponding to the following thresholds for strongly correlated water quality indicators: turbidity (Turb) ≤7.46-16.14 NTU (for all water bodies), SS≤18.42-43.41 mg/L (for river channels outside embankments), and TP≤0.052-0.099 mg/L (for lakes). [Conclusion] Recommendations are proposed for future transparency enhancement projects in the pilot zone: for lakes, control land-based phosphorus input; for river channels outside embankments, enhance bottom sediment stabilization under navigation disturbances; for river channels within embankments, emphasize the algae-suppressing function of submerged vegetation, highlighting the synergistic effect of ecological restoration on transparency management.
[Objective] Surface runoff and soil erosion during rainfall events are the main drivers of phosphorus (P) loss in watersheds, particularly during the rainy season when a few key heavy rainfall events can dominate annual phosphorus load outputs. However, the characteristics of phosphorus loss, influencing factors, and lag effects during different intensities of typical rainfall events in the rainy season remain to be further explored. This study aims to understand the characteristics and influencing factors of phosphorus loss under various magnitudes of typical rainfall events and to analyze the phosphorus loss process during dominant rainfall events. [Methods] During the 2022 and 2023 rainy seasons, five rainfall events (E1-E5) of varying intensities were monitored at the outlet of the Fengyu River sub-watershed, a typical agricultural watershed in the Erhai Lake Basin, Yunnan Province. The rainfall types for events E1-E5 were moderate rain, light rain, moderate rain, heavy rain, and heavy rain. A total of 265 water samples were collected to determine three forms of phosphorus: total phosphorus (TP), total dissolved phosphorus (DP), and particulate phosphorus (PP). Redundancy analysis was used to explore the relationships between phosphorus concentrations/loads and rainfall-runoff characteristics, identifying the key factors influencing phosphorus output and its process. Lag analysis was applied to reveal the hydrological processes behind phosphorus loss. [Results] The results indicated that: (1) The trends of TP and PP concentrations were consistent with flow changes across different types of rainfall events. (2) Total rainfall, rainfall duration, peak flow, and maximum 30-minute rainfall intensity were positively correlated with phosphorus concentrations, while antecedent rainfall index was negatively correlated. (3) Particulate phosphorus dominated the phosphorus loss during rainfall events, accounting for 67%-93% of the total. (4) There was no uniform lag effect between TP, PP, and DP concentrations and discharge. TP and PP shared similar lag effects, indicating that phosphorus primarily originated from surface runoff. [Conclusion] Changes in phosphorus concentrations during rainfall events are influenced by rainfall magnitude, intensity, and antecedent soil conditions. Concentrations and loads of all phosphorus forms were strongly correlated with rainfall duration, total rainfall, peak flow, and 30-minute maximum intensity (I30). The relationship between nutrient concentration and discharge is jointly determined by total rainfall, rainfall duration, antecedent conditions, and hydrological regime. By identifying the characteristics of phosphorus output under various rainfall events during the rainy season, this study provides insights into phosphorus load contributions and supports the control of phosphorus pollution and eutrophication in watershed water bodies.
[Objective] In practical remediation projects, leaching heavy metal-contaminated soils with high clay content is highly challenging. This is not only due to the low permeability of high-clay-content soils, but also because of the unclear influencing patterns and mechanisms of clay content on soil leaching. Current studies on the effects of clay content primarily focus on mixtures of sand and fine-grained soils, lacking systematic investigations into clay soils. Moreover, previous studies investigate the physicomechanical properties of soils with different clay contents, without comparing their effects on heavy metal adsorption and desorption. Studies on the correlation between heavy metal and clay content rely on field sampling methods. However, due to varying soil samples and contamination types, along with complex influencing factors, the conclusions are inconsistent. Therefore, this study intends to artificially prepare soil samples with different clay contents to eliminate complex influencing factors, investigate differences in their leaching performance and geotechnical properties, and analyze their correlations. In doing so, the single-factor influencing pattern of clay content can be obtained. [Methods] Based on the principle that soil particles of different sizes had different settling speeds in solution, soil samples with clay contents of 20%, 30%, 40%, and 50% were prepared via sedimentation method. First, the basic physical properties of soil samples were analyzed, followed by consolidation tests to investigate the porosity ratios, compression characteristics, permeability, and consolidation behaviors of soils with different clay contents, as well as their microscopic characteristics under scanning electron microscope (SEM). Through batch oscillation-centrifugation experiments, the adsorption of heavy metals (Cu and Zn) by the soil samples and their desorption characteristics during heavy metal removal using citric acid were studied, with analysis incorporating pH values and particle size variations. [Results] Soils with different clay contents exhibited significant differences in physicomechanical properties. Soils with a high clay content had larger specific surface areas, lower relative densities, more muscovite and chlorite minerals, and fewer quartz and albite minerals. Additionally, these soils had higher liquid-plastic limits and greater compressibility, while showing lower permeability and porosity ratios, with more soil particle aggregates observed microscopically. The increase in clay content significantly enhanced the soil’s adsorption capacity for heavy metal ions, while deteriorating the desorption performance of citric acid during leaching. As the clay content increased from 20% to 50%, the maximum heavy metal adsorption increased by up to 50%, whereas the maximum desorption rate decreased by up to 20%. Notably, pronounced differences were observed between 20% and 30% clay contents, mainly attributed to the formation of numerous aggregates during this stage, which enhanced the adsorption performance of the soil for heavy metals. In addition, the correlations of clay content with Zn and Cu differed. Zn was more difficult to remove than Cu in high-clay-content contaminated soils. [Conclusions] The experimental findings demonstrate that the differences in various physicomechanical and adsorption-desorption characteristics caused by different clay contents significantly influence the selection of technologies and parameters for soil leaching. Therefore, practical remediation projects must integrate relevant research and experimental analyses to fully consider the effects of clay content, so as to better achieve the goals of contaminated soil remediation.
Biochar is an environmentally friendly soil modifier due to its porous and high specific surface area. To investigate its impact on the water-holding capacity of red clay and the growth of common slope grass species, we selected red clay from Guilin as the research subject. Different types and dosages of biochar were incorporated into the red clay. Subsequently, water-holding capacity tests, pot-planting tests, and pH tests were conducted. Scanning electron microscopy (SEM) was employed to elucidate the mechanism by which biochar affects the water-holding capacity of red clay. Results revealed that the saturated water-holding capacity and pH value of red clay increased with the rising content of four types of biochar, effectively improving the environmental conditions for plant growth. Specifically, adding biochar increased the germination number and plant height of grass seeds. However, a biochar content exceeding 5% negatively affected the growth of grass seeds. Microscopic tests indicated that biochar filled the pores between red clay aggregates, thereby enhancing the saturated water-holding capacity of red clay thanks to its porosity and hydrophilicity.
To investigate the effect of sand content on the growth of slope ecological restoration plants, we used the Analytic Hierarchy Process to select suitable plant species and then conducted planting experiment with sand added in Yili loess slopes. By analyzing changes in plant coverage, cumulative soil evaporation, and maximum crack rate, we found that adding sand to the planting soil can speed up plant germination and improve the soil germination rate. During early growth stage with sufficient water supply, the germination rate and plant coverage are positively correlated with sand content. Nevertheless, under drought conditions, plant coverage decreases as sand content rises. The cumulative evaporation of soil moisture is positively correlated with sand content and varies significantly with temperature fluctuations. Higher temperatures lead to larger differences in cumulative evaporation among samples with different sand contents, but these differences gradually narrow as the temperature drops. Taking 40% sand content as the threshold for optimal conditions: when sand content is below 40%, it is positively correlated with the maximum crack rate, and an increase in the maximum crack rate corresponds to an increase in the peak plant coverage of each sample. However, when sand content exceeds 40%, sand content and the maximum crack rate display a negative correlation. As maximum crack rate increases, the peak plant coverage of sample decreases. For wild or poorly maintained ecological restoration sites, an optimal sand content of 20% is recommended. For artificially maintained ecological restoration sites, a 60% sand content is optimal. In flat, human-intervened ecological restoration and maintenance sites, full sand coverage is the best choice.
[Objective] Urban flooding severely threatens social security and development, and identifying key influencing factors of urban flooding is fundamental to studying flood disasters. Many studies have used the Geographically Weighted Regression (GWR) model to analyze the causes of urban flooding, but its limitation lies in ignoring the scale variations in spatial heterogeneity in various influencing factors. The Multi-scale Geographically Weighted Regression (MGWR) model overcomes this limitation, but few studies have applied MGWR to analyze the relationship between the degree of urban flooding and key influencing factors. This study uses the MGWR model to analyze the key influencing factors of urban flooding in Wuhan and explores the spatial differences in the correlation between these factors and flood severity.[Methods] The central urban area of Wuhan was selected as the study area, and flood point data from 2016 were collected. Elevation and slope were chosen to reflect the impact of terrain on urban flooding, while eight land use types (farmland, forest, grassland, wetland, water body, impervious surface, shrubland, and bare land) were selected to reflect the impact of land use on urban flooding. River density was chosen to represent the impact of the river network on flooding. Global Ordinary Least Square (OLS), GWR, and MGWR were used to analyze the relationships between influencing factors and flood severity.[Results] After screening using OLS, the selected influencing factors for GWR and MGWR analysis were farmland area, grassland area, and impervious surface area. The model performance comparison revealed that the MGWR model outperformed both GWR and OLS. The MGWR showed that the correlation between influencing factors varied across spatial scales. The impact of impervious surface area had the smallest spatial scale, with a bandwidth of 43; the impact of farmland area had a smaller spatial scale, with a bandwidth of 71; and the impact of grassland area and the constant term was close to the global scale, with a bandwidth of 163. Impervious surface area positively influenced the degree of flooding, and it was the most significant factor affecting flooding, with a mean regression coefficient of 0.934. The largest regression coefficients were found in the Wuchang and the central areas of Hongshan District, indicating the highest flood risk there. Farmland area and grassland area negatively influenced the degree of flooding, with the mean regression coefficient for grassland area at -0.280 and for farmland area at -0.241.[Conclusion] The MGWR model considers the varying impact scales of different variables, and the degree of flooding is highly sensitive to impervious surface area, with strong spatial heterogeneity. Impervious surface area positively affects the degree of flooding, while farmland area and grassland area negatively affect it. Among all influencing factors, impervious surface area is the most significant factor affecting the degree of flooding, followed by grassland and farmland areas. The study demonstrates that the MGWR model provides significant improvements over the GWR model and is well-suited for studying the influencing factors of urban flooding.
[Objective] This study took Hanjiang River Basin as the study area. To better monitor the runoff conditions in Hanjiang River Basin, the daily runoff data collected from Ankang and Baihe hydroelectric power stations were selected for prediction analysis. The original data included daily runoff from January 2005 to December 2012. [Methods] This study first employed Multivariate Variational Mode Decomposition(MVMD) to decompose the original daily runoff data from the two stations, reducing data complexity. Subsequently, the decomposed modes and the historical runoff data from the previous 7 days were reconstructed using the Pearson correlation coefficient method(used to measure inter-variable correlation). The modes with high correlation coefficients were superimposed and defined as fluctuation terms, while those with low correlation coefficients were superimposed and defined as random terms. For the prediction of fluctuation terms, the historical runoff from the previous 7 days was used as input, resulting in seven operating conditions. Then, the Microbial Enhanced Algorithm-Back Propagation(MEA-BP) model was used for multiple predictions, and the average values were taken, and evaluation indicators were employed to assess the seven operating conditions. For the prediction of random terms, the Grey Wolf Optimizer-Extreme Learning Machine(GWO-ELM) was used for multiple predictions, and the average values were taken, and evaluation indicators were also used for assessment. Finally, the predicted results were fused, and evaluation coefficients were derived using evaluation indicators, demonstrating the accuracy and stability of the model. [Results] For Ankang station, IMF1 and IMF5 showed correlation coefficients greater than 0.5 with R1-R7, indicating high correlation. Therefore, IMF1 and IMF5 were reconstructed as fluctuation terms. IMF2, IMF3, IMF4, and IMF6, with correlation coefficients all below 0.5 with R1-R7, were reconstructed as random terms. Similarly, for Baihe station, IMF1 and IMF5 had correlation coefficients exceeding 0.5 with R1-R7 and were reconstructed as fluctuation terms, while IMF2, IMF3, IMF4, and IMF6, with correlation coefficients all below 0.5 with R1-R7, were reconstructed as random terms. For the prediction of fluctuation terms, the seven operating conditions were specifically defined as: R1,R1-R2,R1-R3, R1-R4,R1-R5, R1-R6,and R1-R7. The coefficients of determination(R2) for these seven conditions of fluctuation term prediction at Ankang station were 0.54, 0.73, 0.74, 0.72, 0.81, 0.73, and 0.60, respectively, while those at Baihe station were 0.65, 0.68, 0.72, 0.77, 0.82, 0.74, and 0.77, respectively. The optimal operating condition for both stations was condition 5(R1-R5). For the prediction of random terms, the R2 for random term prediction at Ankang and Baihe stations was 0.80 and 0.74, respectively. Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.
[Objective] To address the mismatch between traditional rainfall analysis methods (April to October) for hilly irrigation areas in south China and actual intra-seasonal water demand during rice growth stages (late rice from July to October), this study focuses on intra-seasonal rainfall during the rice growth stages, integrating GIS technology to investigate the water supply reliability of the Maweizao irrigation area. [Methods] Using daily meteorological data from 1989 to 2019 in the irrigation area, the intra-seasonal rainfall frequency analysis method was employed to identify typical representative years and characteristic values for normal years (P=50%), moderately dry years (P=75%), and dry years (P=90%). The FAO Penman-Monteith method and water balance method were then used to calculate the crop water requirements and net irrigation water requirements for rice. [Results]The results showed that: (1) In dry years, the intra-seasonal rainfall during the late rice growth stages (160 mm) accounted for only 21.2% of the total rainfall from April to October (755 mm). Moreover, a mismatch was observed between the rainfall peak (August) and the critical water demand period (booting to heading stage, September). This led to 14% higher net field irrigation water requirements (560 mm) calculated by intra-seasonal rainfall frequency analysis compared to traditional methods, accurately reflecting the typical contradiction in hilly irrigation areas where there was “no rain during water demand periods but excessive rain during non-demand periods.” (2) GIS-based spatial simulations revealed a distinct bimodal structure in the irrigation area during dry years. Croplands near the main water source (Maweizao Reservoir) benefited from sufficient storage capacity (27.02 million m3) and a canal system integrity rate above 85%, achieving a water supply reliability rate greater than 80%, thus forming a high-yield and stable-production core zone. Areas dependent on small reservoirs for water regulation and storage, where storage capacity utilization declined to 60% due to sedimentation, had a water supply reliability rate of 60%-80%. Limited by scattered ponds (406 ponds), insufficient catchment areas (<5 km2 per pond), and damaged main and lateral canals (integrity rate <40%), the overall reliability rates dropped below 40%, posing a high risk of yield reduction. (3) For every 10% increase in water supply reliability rate, late rice yield increased by 35-50 kg per mu(1mu≈666.67 m2), showing a significant positive linear correlation (R2=0.89). When the reliability rate exceeded 80%, soil water content remained stable at 18%-24% (optimal range for rice growth), resulting in yields of 400-500 kg per mu.When the reliability rate fell below 40%, soil water content dropped sharply below 10%, leading to plant wilting or even total crop failure (yield <200 kg per mu). Within the 60%-80% range of reliability rate, each 1 m3 irrigation water increase produced an extra 1.2-1.5 kg of rice, indicating optimal resource use efficiency. [Conclusion] By focusing on intra-seasonal rainfall during rice growth stages, this study reveals the underlying mechanism of irrigation water supply-demand imbalance in hilly irrigation areas and proposes the following three practical strategies. Over 70% irrigation water should be allocated during the booting to heading stages (September) based on crop water requirements, with priority given to areas maintaining water supply reliability rates above 60%. For areas with water supply reliability rates below 40%, the “pond desilting + intelligent water control” project should be implemented to increase small water source utilization rate from 45% to 75%, while restoring main and lateral canals to achieve an integrity rate above 60%. By focusing on intra-seasonal rainfall during rice growth stages, this study provides a scientific basis for precise irrigation management and confirmation of agricultural water use rights in hilly irrigation areas, holding important practical significance for optimizing water resource allocation and enhancing grain production capacity.
[Objective] Taking inline cylindrical emitters as the research object, this study modifies the inclination angle of the emitter’s sidewall end face to investigate the effects of structural optimization on local head loss in drip irrigation pipes. [Methods] The end faces of the inline cylindrical emitters were structurally optimized, with inclination angles set as explanatory variables at four levels: 15°, 30°, 45°, and 90°. Irrigation experiments and numerical simulations were conducted, and the results were processed using the principle of dimensional homogeneity and multiple regression analysis. [Results] The results showed that the velocity and pressure gradients in the convergent and divergent sections of the drip irrigation pipe decreased as the inclination angle of the emitter end face decreased. Based on the principle of dimensional homogeneity and multiple regression analysis, a calculation model for local head loss in drip irrigation pipes incorporating the inclination angle of emitter end face was established. The local head loss was found to be inversely proportional to the 0.706 power of the cotangent of the inclination angle. Case analysis demonstrated that for a 60-m drip irrigation pipe with 0.6-m emitter spacing, the local head loss at inclination angles of 15°, 30°, and 45° decreased to 26.0%, 44.7%, and 65.0% of that at 90°, respectively. For a 60-m drip pipe with 1-m emitter spacing, the local head loss at inclination angles of 15°, 30°, and 45° decreased to 29.6%, 48.1%, and 74.1% of that at 90°, respectively. [Conclusion] In conclusion, the inclined design of the emitter’s end face can significantly reduce local head loss in drip irrigation pipes. Considering manufacturing complexity and cost, an inclination angle of 15° is recommended. These findings can provide references for drip irrigation design and pipe network optimization.
[Objective] Under the actual filling conditions of high rockfill dams, rockfill materials are typically subjected to complex three-dimensional stress states. This study aims to investigate the effects of spherical stress (p), intermediate principal stress coefficient (b), and initial dry density ( ρ0) on the stress-strain relationships, strength characteristics, and non-coaxiality of stress-strain increment directions on the π-plane of rockfill materials. [Methods] Consolidated-drained true triaxial shear tests were conducted on typical rockfill materials for dam construction with constant p and constant b stress paths under three-dimensional conditions involving different p, b, and ρ0. Based on experimentally measured data, conventional strength criteria considering intermediate principal stress effects were comparatively analyzed for their applicability to rockfill material strength. [Results] The results showed that: (1) as p increased, the q- ε1 relationship curves exhibited a progressively steeper strain-hardening trend. The initial shear modulus (Ei) increased correspondingly, and peak shear strength (qmax) significantly enhanced. Shear contraction grew while dilation development was suppressed, and the failure stress ratio (Mb) gradually decreased as p increased. (2) With increasing b, both Ei and qmax progressively declined. Reduced shear contraction made the rockfill materials transition more rapidly into dilation, with increasingly significant dilatancy. Mb demonstrated a downward trend. (3) As ρ0 increased, both Ei and qmax increased markedly. Rockfill materials entered dilation earlier with progressively greater dilatancy, and Mb exhibited an upward trend. [Conclusion] The conclusions are as follows: (1) an increase in p significantly enhances the shear strength of rockfill materials, and the influence of b on its strength progressively diminishes. As ρ0 rises, both the initial shear modulus and shear strength increase markedly, highlighting the necessity for strict quality control during dam construction. (2) The Lade-Duncan strength criterion effectively characterizes the nonlinear strength characteristics of rockfill materials, while the Mohr-Coulomb criterion yields conservative predictions due to its neglect of intermediate principal stress effects. (3) Non-coaxiality between stress and strain increment directions is observed on the π-plane during testing. This non-coaxial behavior is most pronounced during the initial shear stage, and it gradually transitions toward coaxiality as the specimen approaches instability failure. (4) The non-coaxiality of rockfill materials initially increases and then decreases with increasing b. It gradually weakens with increasing p, with the weakening rate diminishing, and it intensifies with higher ρ0 with a progressively faster intensifying rate.
[Objectives] The silt foundations of Qiantang River seawalls exhibit weak impermeability and are prone to water erosion and loss. During periods of strong tidal bores and floods, soil flowing and piping are likely to occur, leading to seawall defects and seepage deformation or cavities in the seawall foundation. To address these issues, solidification and improvement measures are necessary. [Methods] This paper focuses on the different improvement properties of curing agents and employs a controlled-variable method to conduct silt solidification ratio experiments. The improvement of solidified silt were analyzed through unconfined compressive strength tests and permeability tests. XRD was employed for changes in mineral composition and chemical products before and after silt solidification, and SEM tests were conducted to observe the microstructural changes caused by the addition of chemical reagents. ImageJ software with machine learning capabilities was utilized to process SEM images to quantify the correlation between mechanical properties and microstructural characteristics. [Results] The optimal solidifying agent composition consisted of 4% cement, 1% fly ash, 1% lignin, 1% HV, and 1% CMC. This formulation resulted in a 28-fold increase in failure strain and a lower permeability coefficient than that of the original silt. In a permeable environment, the permeability coefficient of the solidified silt gradually decreased over time until it stabilized. SEM revealed hydrated calcium silicate (C-S-H) and ettringite (AFt) from cement hydration in the solidified silt, as well as glassy silica-alumina in a spherical fly ash morphology filling the pores. Quantitative analysis using Image J software indicated that the C4H1-solidified silt exhibited the greatest increase in failure strain and porosity, achieving the best ductility effect. Curve-fitting uncover that the correlation between pore count and strength in the modified solidified silt was not significant, while failure strain showed a positive correlation with porosity. [Conclusion] By transcending the limitations of traditional research, which often focuses on a single property (strength or impermeability), this study achieves synergistic improvement of both high ductility and impermeability, providing a more comprehensive solution for engineering applications. Additionally, the use of ImageJ software for quantitative analysis of pore structure has revealed a positive correlation between porosity and failure strain, offering a microscopic explanation for macroscopic properties.
A series of physical property tests, consolidation tests, and unloading-reloading tests were conducted on undisturbed soil samples of silty clay, silt, and fine sand from the first-stage terrace of Yangtze River in Wuhan. The indoor experimental values of modified Mohr-Coulomb model parameters, including , , ,c',φ',and Rf for typical soil layers with upper clay layer and lower sand layer in this terrace, were directly acquired. Using experimental data, adjusted experimental data, and empirical data from other regions in China, the relationships among different modulus parameters of typical soil layers in this region were analyzed. Moreover, the effective strength indexes were compared with the current provincial standard specification. The parameters obtained from this experimental study can be comprehensively selected and applied in areas with similar engineering geological background conditions. Additionally, they can offer valuable references for geotechnical engineering finite element parameter inversion analysis, parameter sensitivity analysis, and parameter applicability correction, which are based on the finite - element modeling experience of actual foundation pit engineering and the monitoring data of foundation pit engineering examples.
[Objective] The western regions of China are home to vast seasonal frozen soil areas. The unregulated discharge of industrial wastewater in these regions has resulted in soil contamination with heavy metal ions. Under negative temperature conditions, unsaturated soils exhibit complex water migration and phase transition processes. This study aims to study the heat-mass migration and soil deformation in unsaturated lead-contaminated liess under undirectional freezing conditions. [Methods] We utilized theoretical modelling together with laboratory test to investigate the heat, moisture, and pollutant migration patterns and the associated soil deformation characteristics in unsaturated lead-contaminated loess under unidirectional freezing conditions. First, based on the principles of mass conservation, energy conservation, and stress equilibrium, the study developed the water mass conservation equation, pollutant mass conservation equation, energy conservation equation, and soil stress equilibrium equation for lead-contaminated loess under unidirectional freezing conditions. Special attention was given to the impact of the pollutant crystallization process on moisture and heat, as well as the hindrance effect of liquid water phase changes on the soil’s hydraulic conductivity. In addition, the elastic modulus of the soil under freezing conditions was reasonably corrected, and the dynamic transformation of lead acetate crystals during the cooling process was incorporated. Key linking variables, such as the solubility of pollutants and solid-liquid ratio, were introduced. This led to the construction of a multi-field coupling mathematical model that fully reflected the heat-mass migration laws and soil deformation characteristics in contaminated soils. Next, a three-dimensional soil column calculation model was established using COMSOL Multiphysics simulation software to simulate the redistribution processes of moisture, heat, and pollutants in contaminated loess under unidirectional freezing conditions. The study particularly examined the changes in temperature, volumetric water content, and lead ion volumetric molar concentration. Simultaneously, the initial and boundary conditions used in the numerical calculation were applied to actual soil columns, with the model’s reliability verified by laboratory soil column test results. Finally, parameterized analysis systematically explored the impact of factors such as temperature gradient, soil initial saturation, and initial pollutant concentration on pollutant migration, crystallization, and soil deformation. [Conclusion] The study found that: (1) the water-heat-pollutant-force coupling model established in this paper effectively simulated the dynamic migration processes of the temperature field, moisture field, and lead ions in unsaturated loess under negative temperature conditions. Negative temperature induced complex physical and chemical processes within the soil, causing water and pollutant redistribution.(2) Under negative temperature conditions, ice-water phase transitions occurred at the freezing front, with the air pressure slightly lower than the atmospheric pressure. This generated a vacuum suction effect, causing moisture to migrate from the unfrozen zone into the freezing region, further promoting the freezing phase transition. During this migration, pollutants also accumulated in the freezing zone. As the temperature continued to drop, pollutants concentrated, reaching a peak before gradually stabilizing.(3) With an increase in the negative temperature gradient, the intensity of the ice-water phase transition at the freezing front increased, making the vacuum suction effect more pronounced. This led to an increase in the migration of pollutants toward the negative temperature end, causing the pollutants to gradually accumulate in the freezing zone and significantly increasing the amount of pollutant crystallization.(4) Under the same saturation conditions, as the initial concentration of pollutants within the soil increased, the volume of pollutant crystallization under negative temperature conditions also rose. The expansion of pollutant crystals also increased, but compared to the expansion of ice crystals, the effect of pollutant crystallization expansion on soil displacement was not significant.
[Objective] The evolution pattern of temperature field in frozen walls serves as a key factor in optimizing design schemes during artificial ground freezing. At present, laboratory model tests are a critical approach for investigating the development of temperature fields. This study aims to propose a method for deriving similarity criteria for temperature field model tests, offering essential theoretical guidance for the design of laboratory experiments. [Methods] First, analytical solutions to one-dimensional heat conduction differential equations, under both constant and nonlinear thermal parameters, were obtained using the method of separation of variables with different boundary conditions. Based on these solutions, similarity transformation techniques were employed to derive similarity criteria for frozen soil model tests, accounting for both heat exchange and non-heat-exchange conditions. Finally, the finite element software ABAQUS was utilized to conduct numerical simulations of the temperature fields for both prototype and model soils under constant and nonlinear thermal conductivity conditions, verifying the accuracy of the derived criteria. [Results] Results indicated that under non-heat-exchange conditions, when the first-type (Dirichlet) and second-type (Neumann) boundary conditions were combined, the time similarity coefficient equaled the square of the geometric similarity coefficient, enabling rapid determination of model test durations once the geometric scaling ratios were predefined. Similarly, under the combination of second-type and third-type (Robin) boundary conditions, the time similarity constant coefficient remained the square of the geometric similarity constant coefficient. This consistency held regardless of whether thermal parameters were constant or nonlinear, meaning that the time similarity coefficient was the square of the heat conduction geometric similarity coefficient. ensuring uniform criteria between prototype and model cases. When heat exchange was considered, the temperature similarity coefficient was no longer constant. In such cases, the test soil must be replaced and the similarity coefficients of thermal properties such as thermal conductivity, specific heat capacity, and density must satisfy specific quantitative relationships with those of the prototype soil. [Conclusion] The simulation results showed that under the corresponding time and geometric scaling conditions derived in this study, the temperature fields of the prototype and model closely matched, further validating the accuracy of the proposed similarity criteria. The similarity criteria derived from analytical solutions to heat conduction equations fully incorporate the effects of heat exchange boundary conditions and provide a fast and accurate method for determining scaling relationships when similarity coefficients for relevant thermophysical parameters are known. These findings are expected to offer a theoretical basis for solving nonlinear heat conduction problems and for guiding the design and execution of frozen soil model tests.
[Objective] To address the need for improving the mechanical properties and water stability of silt subgrade, this study takes silt stabilized with alkali-activated rice husk ash (RHA) geopolymer as study object and investigates its reinforcement mechanisms and engineering applicability, aiming to determine the optimal combination of activator concentration and RHA dosage.[Methods] NaOH solution and RHA were used synergistically to stabilize silt. Mix proportions were optimized through compaction tests, and macro-mechanical properties were evaluated via unconfined compressive strength tests and disintegration tests. X-ray diffraction (XRD) was used to analyze the composition of hydration products, and scanning electron microscopy (SEM) was employed to characterize the microstructural evolution, systematically revealing the “activation-cementation-strengthening” mechanism.[Results] The results showed that micron-sized RHA particles effectively filled the pores of the silt, while NaOH activated RHA to generate silicate gels, leading to a denser spatial network structure. Mechanical properties were significantly improved: at a NaOH concentration of 10% and an RHA dosage of 7.5%, the unconfined compressive strength reached 1.501 times that of the control group, and disintegration resistance was remarkably enhanced. The micro-macro performance indicated that the interfacial bonding strength of cementitious products is the main controlling factor for the improvements of compressive strength and disintegration resistance.[Conclusion] The alkali-activated RHA geopolymer achieves coordinated improvement of the mechanical properties and water stability of silt through the combined effects of physical filling and chemical cementation. The optimal mix proportion (10% NaOH+7.5% RHA) provides a low-carbon solution for silt subgrade reinforcement and promotes the resource utilization of solid waste (RHA), demonstrating notable engineering, economic, and environmental benefits.
Traditional models for predicting soil-water characteristic curve (SWCC) based on particle size distribution curve require segmentation of the curve when calculating water content and often neglect the pellicular water (also known as film water) content on the surface of soil particles. This significantly limits the prediction accuracy. To address these issues, this study assumes point-to-point contact between particles, employs the Weibull function to characterize the particle size distribution curve, determines the capillary water content using the Young - Laplace equation, and accounts for the influence of film water content. On this basis, a new SWCC model considering particle size distribution and film water is developed. Twenty-six soil samples from the Unsaturated Soil Database (UNSODA) are selected for validation and comparison with the AP and MV models. The results indicate that the proposed model based on particle size distribution and film water can predict the SWCC more accurately and significantly reduces the prediction error of water content in the high-matrix-suction section.
[Objective] Dam deformation results from the nonlinear effects of multiple complex environmental factors. Traditional mathematical models for dam deformation monitoring have difficulty reflecting the complex nonlinear relationships between effect variables and environmental variables, often leading to unsatisfactory prediction results. By leveraging the long-short-term memory (LSTM) model and particle swarm optimization (PSO) algorithm from artificial intelligence technology, a combined PSO-LSTM dam deformation prediction model is established, offering a novel approach for enhancing the accuracy of dam deformation prediction. [Methods] By applying PSO for global optimization of LSTM hyperparameters, a combined PSO-LSTM dam deformation prediction model was established. This method both addressed the deficiencies of traditional prediction models in describing nonlinearity between variables and enhanced the appropriateness of LSTM hyperparameter values. The specific methods included: constructing environmental variable factors based on the interaction mechanism between dam deformation and environmental variables; inputting deformation training sets to determine the range of hyperparameters to be optimized and training the network hyperparameters using the LSTM model; setting the particle position information as the hyperparameters to be optimized and using the PSO algorithm to optimize the LSTM hyperparameters; and outputting dam deformation predicted values at different prediction time points using the parameters obtained from training. [Results] Utilizing deformation monitoring data from concrete gravity dams and concrete arch dams, this study established a traditional monitoring statistical model, a standalone LSTM prediction model, and a combined PSO-LSTM model. The results showed that: (1) the combined PSO-LSTM model achieved the smallest RMSE and MAE values and the largest R2 value, indicating excellent prediction accuracy. Compared to statistical models for monitoring and standalone LSTM models, it demonstrated significantly improved prediction performance. (2) Due to its strong nonlinear learning capabilities, the combined PSO-LSTM model could effectively extract nonlinear characteristics from complex datasets, thereby achieving good prediction performance even with poor-quality deformation monitoring data. [Conclusion] (1) The combined prediction model established based on LSTM and PSO algorithms effectively extracts nonlinear characteristics between environmental variables and effect variables, leading to improved prediction performance. (2) The PSO-LSTM prediction model demonstrates good versatility. Its fundamental principles apply not only to concrete dams but also to earth-rock dams and other hydraulic engineering projects. However, when applying the model, the configuration of neurons in the LSTM model’s input layer must be tailored to the structural characteristics, operational conditions, and influencing factors of different dam types.
[Objective] Since the impoundment of the Three Gorges Dam in 2003, many cataclastic bedding landslides in the reservoir area have been reactivated due to the influence of external factors such as reservoir water level fluctuations, variations in groundwater levels, and rainfall. These landslides are typically large in scale, exhibit complex deformation mechanisms, and pose significant challenges for early warning and disaster prevention. This paper attempts to establish an interaction model linking rainfall, reservoir water, and groundwater with groundwater as the main triggering factor of landslide deformation, and to further reveal the dynamic migration patterns of groundwater under the coupled effects of reservoir water level fluctuations and rainfall. [Methods] The study took the Muyubao Landslide, a cataclastic bedding landslide in the Three Gorges Reservoir area, as a case study. By integrating data statistics with field investigations, a statistical analysis was conducted on nearly seven years of manual and automated monitoring data, field investigation materials, and hydrometeorological information to investigate the quantitative relationship among reservoir water level, rainfall, and groundwater level, as well as the interaction between groundwater level and slope displacement and deformation. [Results] The research results indicated that: (1) A groundwater level of 175 meters at the front platform of the slope served as the critical threshold for the initiation of landslide deformation. When the groundwater level at the front platform approached 175 m, deformation began under the influence of buoyancy-induced weight reduction. When the groundwater level at the front platform exceeded 175 m, both buoyancy-induced reduction and dynamic water pressure acted on the slope, with the effect of dynamic water pressure intensifying as the groundwater level rose.(2) Statistical analysis of monitoring data revealed thresholds for rainfall-induced groundwater level rise. Ten consecutive days of rainfall totaling 150 mm increased the groundwater level at the front of the slope by 3.22 m to 6.88 m. In the case of 300 mm of cumulative rainfall within 30 days, the groundwater level at the front of the slope increased by approximately 10 m. A “lag effect” was observed in groundwater response to rainfall, typically lasting 3 to 13 days.(3) From October to December 2017, rainfall occurred on 27 out of first 32 days, totaling 310.6 mm. As a result, the groundwater level in borehole QSK1 at the front platform of the slope rose to 184.2 m, nearly 10 m above the highest reservoir water level (175 m). Over the 72-day period, the slope displacement totaled 88.5 mm. [Conclusion] (1) Groundwater level fluctuations significantly precede slope deformation. Given known reservoir water levels, it is possible to forecast groundwater level based on reservoir water level and rainfall data, and further predict slope deformation based on the groundwater level. This approach provides a strong basis for landslide early warning and prediction.(2) The effective contribution of rainfall to groundwater recharge varies with different types of rainfall. Compared to intense rainstorms, prolonged and continuous rainfall causes a more significant rise in groundwater levels, especially around periods of high reservoir water levels, posing greater risks to slope stability. Therefore, in landslide disaster prevention, the role of rainfall and groundwater should be carefully considered. It is crucial to optimize the layout of monitoring points, enhance real-time automated groundwater monitoring capacity and service quality, and better understand the impact of groundwater dynamics on slope deformation.
