Search Results (2,677)

To study and quantify the impact of water storage on lake slope stability after the closure of an open-pit mine, we targeted slope control measures by large-scale parallel computing methods and strength reduction theory. This was based on a three-dimensional refined numerical model to simulate the evolution of slope stability under different water storage levels and backfilling management conditions, and to quantitatively assess the risk of slope instability through the spatial distribution of stability coefficients. This study shows that during the impoundment process, the slope stability has a nonlinear decreasing trend due to the decrease in effective stress caused by the increase in pore water pressure. When the water storage was at 0 m, the instability range is the largest, and the surface range is nearly 200 m from the edge of the pit; when the water level continued to rise to 50 m, the hydrostatic pressure of the pit lake water on the slope support effect began to appear, and the stability was improved, but there is still a wide range of unstable areas at the bottom. In view of the unstable area of the steep slope with soft rock in the north slope during the process of water storage, the management scheme of backfilling the whole bottom to −150 m was proposed, and the slope protection and pressure footing were formed by discharging the soil to −40 m in steps to improve the anti-slip ability of the slope. Full article

Cement–Soil Mixing (CSM) Pile is an important technology for soft ground reinforcement, and its as-formed compressive strength directly affects engineering design and construction quality. To address the significant discrepancy between laboratory-tested strength and field as-formed strength arising from differing environmental conditions, this study conducted modified laboratory experiments simulating key field formation characteristics. A cement–soil preparation system considering actual immersion conditions was established, based on controlling the initial water content state of the foundation soil before pile formation and applying submerged conditions post-formation. Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. Engineering validation demonstrated that the model achieved an RMSE of 0.138, an MAE of 0.112, and an R² of 0.961. It effectively addresses the issue of large prediction deviations caused by insufficient environmental simulation in traditional mix proportion tests. The research findings establish a quantitative relationship between as-formed strength and preparation parameters, providing an effective experimental improvement and strength prediction method for the engineering design of CSM Pile. Full article

As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and plant physiological activities. Existing studies have made significant advancements in simulating LAI, yet accurate LAI simulation remains challenging. To address this challenge and gain deeper insights into the environmental controls of LAI, this study aims to accurately simulate LAI in the Loess Plateau using deep learning models and to elucidate the spatiotemporal influence of soil moisture and temperature on LAI dynamics. For this purpose, we used three deep learning models, namely Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), and Interpretable Multivariable (IMV)-LSTM, to simulate LAI in the Loess Plateau, only using soil moisture and temperature as inputs. Results indicated that our approach outperformed traditional models and effectively captured LAI variations across different vegetation types. The attention analysis revealed that soil moisture mainly influenced LAI in the arid northwest and temperature was the predominant effect in the humid southeast. Seasonally, soil moisture was crucial in spring and summer, notably in grasslands and croplands, whereas temperature dominated in autumn and winter. Notably, forests had the longest temperature-sensitive periods. As LAI increased, soil moisture became more influential, and at peak LAI, both factors exerted varying controls on different vegetation types. These findings demonstrated the strength of deep learning for simulating vegetation–climate interactions and provided insights into hydrothermal regulation mechanisms in semiarid regions. Full article

Rural roads are critical for connecting isolated communities to essential services such as education and health and administrative services, as well as production and market opportunities in low-income countries. More than 70% of movements of people and goods in Sub-Saharan Africa are heavily reliant on rural transport systems, using both motorised but mainly alternative means of transport. However, rural roads often suffer from poor construction due to the use of low-strength, in situ soils and limited financial resources, leading to premature failures and subsequent traffic disruptions with significant economic losses. This study investigates the use of rice husk ash (RHA), a waste byproduct from rice production, as a sustainable supplement to Ordinary Portland Cement (OPC) for soil stabilisation in order to increase durability and sustainability of rural roads, hence limit recurrent maintenance needs and associated transport costs and challenges. To conduct this study, soil samples collected from Mulungushi, Zambia, were treated with combinations of 6–10% OPC and 10–15% RHA by weight. Laboratory tests measured maximum dry density (MDD), optimum moisture content (OMC), and California Bearing Ratio (CBR) values; the main parameters assessed to ensure the quality of road construction soils. Results showed that while the MDD did not change significantly and varied between 1505 kg/m³ and 1519 kg/m³, the OMC increased hugely from 19.6% to as high as 26.2% after treatment with RHA. The CBR value improved significantly, with the 8% OPC + 10% RHA mixture achieving the highest resistance to deformation. These results suggest that RHA can enhance the durability and sustainability of rural roads and hence improve transport systems and subsequently improve socioeconomic factors in rural areas. Full article

In this study, the efficacy of super white cement (SWC) to improve organic soils was researched. For stabilization, 10%, 15%, and 20% proportions of SWC were added to organic soil. After improvement with SWC, Atterberg limit testing, standard Proctor tests, triaxial compression tests, and swelling and compressibility tests were performed on the organic soil. Proctor tests showed that stabilization of organic soil with SWC increased maximum dry density (MDD) and optimum moisture content (OMC) values. After stabilization, the unconfined compressional strength values of the soil increased. This increase continued until the 28th day and had a reducing trend after improvement with SWC, linked to time. In addition to the reaction between SWC and OS, the time-dependent behavior of OS also contributed to this behavior. With the increase in SWC proportions, the cohesion intercept and internal friction angle values rapidly increased until the 56th day. This increase began to reduce after the 56th day. After stabilization, the swelling percentage and compressibility values for the soil reduced. The addition of SWC within organic soil appeared to improve the engineering properties of the soil. Full article

Because artificially cemented granular (ACG) materials employ diverse combinations of aggregates and binders—including cemented soil, low-cement-content cemented sand and gravel (LCSG), and concrete—their stress–strain responses vary widely. In LCSG, the binder dosage is typically limited to 40–80 kg/m³ and the sand–gravel skeleton is often obtained directly from on-site or nearby excavation spoil, endowing the material with a markedly lower embodied carbon footprint and strong alignment with current low-carbon, green-construction objectives. Yet, such heterogeneity makes a single material-specific constitutive model inadequate for predicting the mechanical behavior of other ACG variants, thereby constraining broader applications in dam construction and foundation reinforcement. This study systematically summarizes and analyzes the stress–strain and volumetric strain–axial strain characteristics of ACG materials under conventional triaxial conditions. Generalized hyperbolic and parabolic equations are employed to describe these two families of curves, and closed-form expressions are proposed for key mechanical indices—peak strength, elastic modulus, and shear dilation behavior. Building on generalized plasticity theory, we derive the plastic flow direction vector, loading direction vector, and plastic modulus, and develop a concise, transferable elastoplastic model suitable for the full spectrum of ACG materials. Validation against triaxial data for rock-fill materials, LCSG, and cemented coal–gangue backfill shows that the model reproduces the stress and deformation paths of each material class with high accuracy. Quantitative evaluation of the peak values indicates that the proposed constitutive model predicts peak deviatoric stress with an error of 1.36% and peak volumetric strain with an error of 3.78%. The corresponding coefficients of determination R² between the predicted and measured values are 0.997 for peak stress and 0.987 for peak volumetric strain, demonstrating the excellent engineering accuracy of the proposed model. The results provide a unified theoretical basis for deploying ACG—particularly its low-cement, locally sourced variants—in low-carbon dam construction, foundation rehabilitation, and other sustainable civil engineering projects. Full article

Soft soils, characterized by high compressibility, low shear strength, and high water sensitivity, pose serious challenges to geotechnical engineering in infrastructure projects. Traditional stabilization methods such as lime and cement face limitations, including environmental concerns and poor durability under chemical or cyclic loading. Ionic soil stabilizers (ISSs), which operate through electrochemical mechanisms, offer a promising alternative. However, their long-term performance—particularly under environmental stressors such as acid/alkali exposure and cyclic wetting–drying—remains insufficiently explored. This study evaluates the strength and durability of ISS-modified soil through a comprehensive experimental program, including direct shear tests, permeability tests, and cyclic wetting–drying experiments under neutral, acidic (pH = 4), and alkaline (pH = 10) environments. The results demonstrate that ISS treatment increases soil cohesion by up to 75.24% and internal friction angle by 9.50%, particularly under lower moisture conditions (24%). Permeability decreased by 88.4% following stabilization, resulting in only a 10–15% strength loss after water infiltration, compared to 40–50% in untreated soils. Under three cycles of wetting–drying, ISS-treated soils retained high shear strength, especially under acidic conditions, where degradation was minimal. In contrast, alkaline conditions caused a cohesion reduction of approximately 26.53%. These findings confirm the efficacy of ISSs in significantly improving both the mechanical performance and environmental durability of soft soils, offering a sustainable and effective solution for soil stabilization in chemically aggressive environments. Full article

This study investigates the improvement effect and micro-mechanism of guar gum and palm fibers, two eco-friendly materials, on expansive soil. The study uses disintegration tests, unconfined compressive strength tests, triaxial compression tests, and SEM analysis to evaluate the enhancement of mechanical properties. The results show that the guar gum–palm fiber composite significantly improves the compressive and shear strength of expansive soil. The optimal ratio is 2% guar gum, 0.4% palm fiber, and 6 mm palm fiber length. Increasing fiber length initially boosts and then reduces unconfined compressive strength. Guar gum increases unconfined compressive strength by 187.18%, further improved by 20.9% with palm fibers. When fiber length is fixed, increasing palm fiber content increases and then stabilizes peak stress and shear strength (cohesion and internal friction angle), improving by 27.30%, 52.1%, and 12.4%, respectively, compared to soil improved with only guar gum. Micro-analysis reveals that guar gum enhances bonding between soil particles via a gel matrix, improving water stability and mechanical properties, while palm fibers reinforce the soil and inhibit crack propagation. The synergistic effect significantly enhances composite-improved soil performance, offering economic and environmental benefits, and provides insights for expansive soil engineering management. Full article

This study investigates the synergistic modification of cement–soil using waste brick powder (WBP) and polyvinyl alcohol (PVA) fibers to address the growing demand for sustainable construction materials and recycling of demolition waste. An orthogonal experimental design was employed with 5% WBP (by mass) and PVA fiber content (0–1%), evaluating mechanical properties based on unconfined compressive strength (UCS) and splitting tensile strength (STS) and microstructure via scanning electron microscopy (SEM) across 3–28 days of curing. The results demonstrate that 0.75% PVA optimizes performance, enhancing UCS by 28.3% (6.87 MPa) and STS by 34.6% (0.93 MPa) at 28 days compared to unmodified cement–soil. SEM analysis revealed that PVA fibers bridged microcracks, suppressing propagation, while WBP triggered pozzolanic reactions to densify the matrix. This dual mechanism concurrently improves mechanical durability and valorizes construction waste, offering a pathway to reduce reliance on virgin materials. This study establishes empirically validated mix ratios for eco-efficient cement–soil composites, advancing scalable solutions for low-carbon geotechnical applications. By aligning material innovation with circular economy principles, this work directly supports global de-carbonization targets in the construction sector. Full article

Agricultural soil contaminated with mercury (Hg) poses a serious threat to ecosystems and human health. Although adding an appropriate amount of selenium (Se) can reduce the toxicity and mobility of Hg in soil, Se alone is prone to leaching into groundwater through soil runoff. Therefore, Se-enriched compound fertilizers were developed, and their remediation effect on Hg-contaminated agricultural soil was determined. The Se-enriched compound fertilizers were prepared by combining an organic fertilizer (vinegar residue, biochar, and potassium humate), inorganic fertilizer (urea, KH₂PO₄, ZnSO₄, and Na₂SeO₃), and a binder (attapulgite and bentonite). A material proportioning experiment showed that the optimal granulation rate, organic matter content, and compressive strength were achieved when using 15% attapulgite (Formulation 1) and 10% bentonite (Formulation 2). An analysis of Se-enriched compound fertilizer particles showed that the two Se-enriched compound fertilizers complied with the standard for organic–inorganic compound fertilizers (China GB 18877-2002). Compared with the control, Formulation 1 and Formulation 2 significantly reduced the Hg content in bulk and rhizosphere soil following diethylenetriaminepentaacetic acid (DTPA) extraction by 40.1–47.3% and 53.8–56.0%, respectively. They also significantly reduced the Hg content in maize seedling roots and shoots by 26.4–29.0% and 57.3–58.7%, respectively, effectively limiting Hg uptake, transport, and enrichment. Under the Formulation 1 and Formulation 2 treatments, the total and DTPA-extractable Se contents in soil and maize seedlings were significantly increased. This study demonstrated that Se-enriched compound fertilizer effectively remediates Hg-contaminated agricultural soil and can promote the uptake of Se by maize. The results of this study are expected to positively contribute to the sustainable development of the agro-ecological environment. Full article

This study investigates the effectiveness of geopolymer-based binders for the stabilization of silty sand, aiming to improve its strength and durability under cyclic environmental conditions. A composite binder consisting of Ground Granulated Blast-furnace Slag (GGBS) and Recycled Glass Powder (RGP), modified with nano poly aluminum silicate (PAS), was used to treat the soil. The long-term performance of the stabilized soil was evaluated under cyclic wetting–drying (W–D) conditions. The influence of PAS content on the mechanical strength, environmental safety, and durability of the stabilized soil was assessed through a series of laboratory tests. Key parameters, including unconfined compressive strength (UCS), mass retention, pH variation, ion leaching, and microstructural development, were analyzed using field emission scanning electron microscopy (FE-SEM) and energy-dispersive X-ray spectroscopy (EDS). Results revealed that GGBS-stabilized specimens maintained over 90% of their original strength and mass after eight W–D cycles, indicating excellent durability. In contrast, RGP-stabilized samples exhibited early strength degradation, with up to an 80% reduction in UCS and 10% mass loss. Environmental evaluations confirmed that leachate concentrations remained within acceptable toxicity limits. Microstructural analysis further highlighted the critical role of PAS in enhancing the chemical stability and long-term performance of the stabilized soil matrix. Full article

Previous studies have mostly focused on the adsorption behavior of microplastics for antibiotics in soil or aqueous environments. This study explores the adsorption characteristics of microplastics for antibiotics under groundwater environmental conditions and the influence of typical influencing factors of the groundwater environment (pH, pollutant concentration, aquifer media, dissolved organic matter, and ionic strength) on the adsorption process. Polyethylene (PE) and tetracycline (TC) were selected as typical microplastics and antibiotics in the experiment. The study results showed that the adsorption of TC by PE reached equilibrium at 48 h, and the adsorption kinetics fitted pseudo-second-order kinetics models well. The adsorption isotherm was consistent with the Langmuir model. The adsorption capacity of PE for TC was highest under neutral conditions and positively correlated with the initial concentration of TC. The aquifer media exhibited limited effects on the adsorption process. Fulvic acid (FA) significantly suppressed TC adsorption onto PE, attributable to competitive adsorption mechanisms. TC adsorption on PE initially increased then declined with Ca²⁺ concentration due to Ca²⁺ bridging and competition. This research elucidates the adsorption mechanisms of PE towards TC, providing theoretical basis and reference for assessing the environmental risk of microplastics and antibiotics in groundwater. Full article

In order to study how indigenous microorganisms can enhance the strength properties of granite residual soil in the Hanzhong area, two Bacillus species that produce urease were isolated from the local soil. The two Bacillus species are Bacillus subtilis and Bacillus tequilensis, and they were used for the solidification and improvement of the granite residual soil. Unconfined compressive strength tests, scanning electron microscope (SEM) and X-ray diffraction (XRD) analyses were systematically used to analyze the influence and mechanism of different cementation solution concentrations on the improvement effect. It has been found that with the growth of cementing fluid concentration, the unconfined compressive strength of improved soil specimens shows an increasing tendency, reaching its highest value when the cementing solution concentration is 2.0 mol/L. Among different bacterial species, curing results vary; Bacillus tequilensis demonstrates better performance across various cementing solution concentrations. The examination of failure strain in improved soil samples indicates that brittleness has been successfully alleviated, with optimal outcomes obtained at a cementing solution concentration of 1.0 mol/L. SEM and XRD analyses show that calcium carbonate precipitates (CaCO₃) are formed in soil samples treated by both strains. These precipitates effectively bond soil particles, verifying improvement effects on a microscopic level. The present study proposes an environmentally friendly and economical method for enhancing engineering applications of granite residual soil in Hanzhong area, which holds significant importance for projects such as artificial slope filling, subgrade filling, and foundation pit backfilling. Full article

Fly-ash-based bubble lightweight soil is widely used due to its environmental friendliness, load reduction, ease of construction, and low costs. In this study, 41 sets of 28 d compressive strength data on lightweight soils with different water–cement ratios, blowing agent dosages, and fly ash dosages were collected through a literature search and indoor tests. Using the compressive strength index and SEM tests, the correlation between the mix ratio design and the microscopic particle components was investigated. The findings were as follows: carbonation reactions occurred in lightweight soil during the maintenance process, and the particles were spherical; increasing the dosage of blowing agent increased the soil’s porosity and pore diameter, leading to the formation of through-holes and reducing the compressive strength and mobility; increasing the fly ash dosage and water–cement ratio increased the soil’s mobility but reduced its compressive strength; and the strength decreased significantly when the fly ash dosage was more than 16% (e.g., the strength at a 20% dosage was 17.8% lower than that at a 15% dosage). Feature importance analysis showed that the water–cement ratio (57.7%), fly ash dosage (30.9%), and blowing agent dosage (11.1%) had a significant effect on strength. ExtraTrees, LightGBM, and Bayesian-optimized Random Forest models were used for 28d strength prediction with coefficients of determination (R²) of 0.695, 0.731, and 0.794, respectively. The Bayesian-optimized Random Forest model performed optimally in terms of the mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), and the prediction performance was best. The accuracy of the model is expected to be further improved with expansions in the database. A 28 d compressive strength prediction platform for fly-ash-based bubble lightweight soil was ultimately developed, providing a convenient tool for researchers and engineers to predict material properties and mix ratios. Full article

(1) Background: Wetlands are ecologically significant ecosystems that support biodiversity and contribute to essential environmental functions such as water purification, carbon storage and flood regulation. However, these ecosystems face increasing pressures from land-use change and degradation, prompting the need for scalable and accurate classification methods to support conservation and policy efforts. In this research, our motivation was to test whether high-spatial-resolution PlanetScope imagery can be used with pixel-based machine learning to support the mapping and monitoring of wetlands at a national scale. (2) Methods: This study compared four machine learning classification models—Random Forest (RF), XGBoost (XGB), Histogram-Based Gradient Boosting (HGB) and a Multi-Layer Perceptron Classifier (MLPC)—to detect and map wetland areas across New Zealand. All models were trained using eight-band SuperDove satellite imagery from PlanetScope, with a spatial resolution of ~3 m, and ancillary geospatial datasets representing topography and soil drainage characteristics, each of which is available globally. (3) Results: All four machine learning models performed well in detecting wetlands from SuperDove imagery and environmental covariates, with varying strengths. The highest accuracy was achieved using all eight image bands alongside features created from supporting geospatial data. For binary wetland classification, the highest F1 scores were recorded by XGB (0.73) and RF/HGB (both 0.72) when including all covariates. MLPC also showed competitive performance (wetland F1 score of 0.71), despite its relatively lower spatial consistency. However, each model over-predicts total wetland area at a national level, an issue which was able to be reduced by increasing the classification probability threshold and spatial filtering. (4) Conclusions: The comparative analysis highlights the strengths and trade-offs of RF, XGB, HGB and MLPC models for wetland classification. While all four methods are viable, RF offers some key advantages, including ease of deployment and transferability, positioning it as a promising candidate for scalable, high-resolution wetland monitoring across diverse ecological settings. Further work is required for verification of small-scale wetlands (<~0.5 ha) and the addition of fine-spatial-scale covariates. Full article