Search Results (3,052)

The shear characteristics of the frozen soil–concrete interface are core parameters in frost heave resistance design in cold-region engineering, and the influence mechanism of interface roughness on these characteristics is not clear. In this study, the regulatory effect of different roughness levels (R-0 to R-4) on the interfacial freezing strength was quantitatively analyzed for the first time through direct shear tests, and the evolution characteristics of the contribution ratio of the ice cementation strength were revealed. The results show that the peak shear strength of the interface increases significantly with the roughness (when the normal stress is 400 kPa and the water content is 14%, the increase in R-4 is 47.7% compared with R-0); the ice cementation strength increases synchronously and its contribution ratio increases with the increase in roughness. Although the absolute value of the residual strength increase is small, the relative amplitude is larger (178.5% increase under the same working conditions). The peak cohesion increased significantly with the roughness (R-0 to R-4 increased by 268.6%), while the residual cohesion decreased. The peak and residual internal friction angle increased slightly with the roughness. The study clarifies the differential influence mechanism of roughness on the interface’s shear parameters and provides a key quantitative basis for the anti-frost heave design of engineering interfaces in cold regions. Full article

Previous studies have extensively applied the generalized consolidation theory, which incorporates a two-stress state variable framework, to predict the volumetric behavior of unsaturated expansive soils under varying mechanical stress and matric suction. A key requirement for this approach is a constitutive surface that links the soil void ratio to both net stress and matric suction. A large number of fitting parameters are typically needed to accurately fit a two-variable void ratio surface equation to laboratory test data. In this study, a single-stress state variable framework was adopted to describe the void ratio as a function of effective stress for unsaturated soils. The proposed approach was applied to fit void ratio–effective stress constitutive curves to laboratory test data for two different expansive clays. Additionally, a finite element model coupling variably saturated flow and stress–strain analysis was developed to simulate the volume change behavior of expansive clay subjected to moisture fluctuations. The model utilizes suction stress to compute the effective stress field and incorporates the dependency of soil modulus on volumetric water content based on the proposed void ratio–effective stress relationship. The developed numerical model was validated against a benchmark problem in which a layer of Regina expansive clay was subjected to a constant infiltration rate. The results demonstrate the effectiveness of the proposed model in simulating expansive soil deformations under varying moisture conditions over time. Full article

Mining activity in Peru generates environmental liabilities with the potential to release toxic metals into the environment. This study conducted a comprehensive physical, chemical, mineralogical, and toxicological characterization of ten active and inactive tailings samples from the Arequipa region in southern Peru. Particle size distribution analysis, inductively coupled plasma atomic emission spectroscopy (ICP-AES), scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), and the Toxicity Characteristic Leaching Procedure (TCLP) followed by ICP-MS were employed. The results revealed variable particle size distributions, with the sample of Secocha exhibiting the finest granulometry. Chemically, 8 out of 10 samples exhibited concentrations of at least two metals surpassing the Peruvian Environmental Quality Standards (EQS) for soils with values reaching >6000 mg/kg of arsenic (Paraiso), 193.1 mg/kg of mercury (Mollehuaca), and 2309 mg/kg of zinc (Paraiso). Mineralogical analysis revealed the presence of sulfides such as arsenopyrite, cinnabar, galena, and sphalerite, along with uraninite in the Otapara sample. In the TCLP tests, 5 out of 10 samples released at least two metals exceeding the environmental standards on water quality, with concentrations up to 0.401 mg/L for mercury (Paraiso), 0.590 mg/L for lead (Paraiso), and 9.286 mg/L for zinc (Kiowa Cobre). These results demonstrate elevated levels of Potentially Toxic Elements (PTEs) in both solid and dissolved states, reflecting a critical geochemical risk in the evaluated areas. Full article

The spatial variation of forest ecosystem services at regional scales remains poorly understood, and few studies have explicitly analyzed how ecosystem services are distributed across different forest management types. This study assessed the spatial overlap between forest management types and ecosystem service hotspots in the Southeastern United States (SEUS) and the Pacific Northwest (PNW) forests. We used the InVEST suite of tools and GIS to quantify carbon storage and water yield. Carbon storage was estimated, stratified by forest group and age class, and literature-based biomass pool values were applied. Average annual water yield and its temporal changes (2001–2020) were modeled using the annual water yield model, incorporating precipitation, potential evapotranspiration, vegetation type, and soil characteristics. Ecosystem service outputs were classified to identify hotspot zones (top 20%) and to evaluate the synergies and tradeoffs between these services. Hotspots were then overlaid with forest management maps to examine their distribution across management types. We found that only 2% of the SEUS and 11% of the PNW region were simultaneous hotspots for both services. In the SEUS, ecological and preservation forest management types showed higher efficiency in hotspot allocation, while in PNW, production forestry contributed relatively more to hotspot areas. These findings offer valuable insights for decision-makers and forest managers seeking to preserve the multiple benefits that forests provide at regional scales. Full article

Acacia mearnsii De Wild. has been introduced to over 150 countries for its economic value. However, it easily escapes from plantations and establishes monospecific stands across plains, hills, valleys, and riparian habitats, including protected areas such as national parks and forest reserves. Due to its negative ecological impact, A. mearnsii has been listed among the world’s 100 worst invasive alien species. This species exhibits rapid stem growth in its sapling stage and reaches reproductive maturity early. It produces a large quantity of long-lived seeds, establishing a substantial seed bank. A. mearnsii can grow in different environmental conditions and tolerates various adverse conditions, such as low temperatures and drought. Its invasive populations are unlikely to be seriously damaged by herbivores and pathogens. Additionally, A. mearnsii exhibits allelopathic activity, though its ecological significance remains unclear. These characteristics of A. mearnsii may contribute to its expansion in introduced ranges. The presence of A. mearnsii affects abiotic processes in ecosystems by reducing water availability, increasing the risk of soil erosion and flooding, altering soil chemical composition, and obstructing solar light irradiation. The invasion negatively affects biotic processes as well, reducing the diversity and abundance of native plants and arthropods, including protective species. Eradicating invasive populations of A. mearnsii requires an integrated, long-term management approach based on an understanding of its invasive mechanisms. Early detection of invasive populations and the promotion of public awareness about their impact are also important. More attention must be given to its invasive traits because it easily escapes from cultivation. 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

Prolonged drought and soil degradation severely affect soil fertility and limit crop productivity. Superabsorbent hydrogels offer an effective solution for improving water retention in soil and supporting plant growth. In this work, we examined the performance of superabsorbent hydrogels based on sodium alginate, acrylic acid (AA), and poly (ethylene oxide) (PEO) cross-linked with 12.5 kGy using e-beam irradiation. The hydrogels were assessed in various aqueous environments by examining network characteristics, swelling capacity, and swelling kinetics to evaluate the impact of water’s electrical conductivity (which ranges from 0.05 to 321 μS/cm). Morphological and chemical structure changes were evaluated using SEM and FTIR techniques. The results demonstrated that water conductivity significantly affected the physicochemical properties of the hydrogels. Swelling behavior showed notable sensitivity to electrical conductivity variations, with swelling degrees reaching 28,400% at 5 μS/cm and 14,000% at 321 μS/cm, following first-order and second-order kinetics. FTIR analysis confirmed that structural modifications correlated with water conductivity, particularly affecting the O–H, C–H, and COOH groups sensitive to the ionic environment. SEM characterization revealed a porous morphology with an interconnected microporous network that facilitates efficient water diffusion. These hydrogels show exceptional swelling capacity and are promising candidates for sustainable agriculture applications. Full article

Large soil pores critically influence water and solute transport in soils. The presence of preferential flow paths created by soil macropores can profoundly impact water quality, underscoring the necessity of accurately assessing the characteristics of these macropores. However, it remains unclear whether variations in macropore structure exist between different altitudes and positions of terraced paddy fields. The primary objective of this research was to utilize X-ray computed tomography (CT) and image analysis techniques to characterize the soil pore structure at both the inner field and ridge positions across different altitude levels (high, medium, and low altitude) within terraced paddy fields. The results indicate that there are significant differences in the distribution of large soil pores at different altitudes, with large pores concentrated in the surface layer (0–10 cm) in low-altitude areas, while in high-altitude areas, the distribution of large pores is more uniform. Additionally, as altitude increases, the porosity of large pores shows an increasing trend. The three-dimensional equivalent diameter and large pore volume are primarily characterized by large pores ranging from 1 to 2 mm and 0 to 5 mm³, respectively, with their morphology predominantly appearing spherical or ellipsoidal. The connectivity of large pores in the surface layer of paddy soil is stronger than that in the bunds. However, this connectivity gradually weakens with increasing soil depth. The findings from this study provide valuable quantitative insights into the unique characteristics of soil macropores that vary according to the altitude and position in terraced paddy fields. Moreover, this study emphasizes the necessity for future research that encompasses a broader range of soil types, altitudes, and terraced paddy locations to validate and further explore the identified relationships between altitude and macropore characteristics. Full article

An indicator-based approach was implemented to assess the contributions of soils in supplying ecosystem services, providing a scalable tool for modeling the spatial heterogeneity of soil functions at regional and local scales. The method consisted of (i) the definition of soil-based ecosystem services (SESs), using available point data and thematic maps; (ii) the definition of appropriate SES indicators; (iii) the assessment and mapping of potential SESs provision for the Emilia-Romagna region (22.510 km²) in NE Italy. Depending on data availability and on the role played by terrain features and soil geography and its complexity, maps of basic soil characteristics (textural fractions, organic C content, and pH) covering the entire regional territory were produced at a 1 ha resolution using digital soil mapping techniques and geostatistical simulations to explicitly consider spatial variability. Soil physical properties such as bulk density, porosity, and hydraulic conductivity at saturation were derived using pedotransfer functions calibrated using local data and integrated with supplementary information such as land capability and remote sensing indices to derive the inputs for SES assessment. Eight SESs were mapped at 1:50,000 reference scale: buffering capacity, carbon sequestration, erosion control, food provision, biomass provision, water regulation, water storage, and habitat for soil biodiversity. The results are discussed and compared for the different pedolandscapes, identifying clear spatial patterns of soil functions and potential SES supply. Full article

Climate change negatively affects agriculture, causing desertification, salinisation, and drought. The biochar hydroinfiltrator (ES Patent No.: ES2793448 B2) is a device that increases the capture of rainwater or irrigation water for crops by increasing infiltration rates. Biochar, produced via biomass pyrolysis, has emerged as a promising agricultural amendment, as it helps to optimise moisture retention and improve soil structure, key aspects for boosting crop yields. There is growing interest in microorganisms’ plant-growth-promoting activity (PGP) by carrying out different activities considered growth promoters. The aim of the present study is to evaluate the use of a biochar hydroinfiltrator as a promoter of microbial activity when it is used in soil. Metagenomic analysis of soils with and without the device reveals that genera Bacillus and Sphingomonas became particularly enriched in soils with hydroinfiltrators. Also, in order to understand the interaction between the uses of biochar together with bacteria PGP, an in vitro test was carried out. Two microorganisms, previously selected for their characteristics as plant growth promoters, were inoculated in soils with and without biochar and they grew better after 15 to 30 days of inoculation, showing major CFU counts. This combined strategy—biochar hydroinfiltrator and PGP bacteria—offers an innovative, eco-friendly approach to sustainable agriculture, particularly under drought stress. Full article

This study evaluates the potential health risks posed by geogenic arsenic in environments suitable for leisure activities, such as walking, bathing, and playing, for adults and children alike, as well as in neighbouring agricultural areas. The study includes an analysis of environmental characteristics and the main stream originating in the adjacent mining area, with water and sediment samples taken. The study area is representative of other areas in the vicinity of the Mar Menor Lagoon, which is one of the largest and most biodiverse coastal lagoons in the Mediterranean Sea. The general characteristics of the soil and water were determined for this study, as was the concentration of As in the soil and water samples. A granulometric separation was carried out into four different fractions (<2 mm, <250 µm, <100 µm, and <65 µm). The mineralogical composition, total As content, and bioaccessible As content are analysed in each of these fractions. This provides data with which to calculate the danger of arsenic (As) to human health by ingestion and to contribute to As bioaccessibility studies and the role played by the mineralogical composition and particle size of soil ingestion. The conclusions rule out residential use of this environment, although they allow for eventual tourist use and traditional agricultural use of the surrounding soils. Full article

The use of the Soil and Water Assessment Tool (SWAT) model driven by China Meteorological Assimilation Driving Datasets (CMADS) for runoff simulation research is of great significance for regional flood prevention and control. Therefore, from the perspective of production-living-ecological space, this article combined multi-source data such as DEM, soil texture and land use type, in order to construct scenarios of territorial spatial change (TSC) across distinct periods. Based on the CMADS-L40 data and the SWAT model, it simulated the runoff dynamics in the Xitiaoxi River Basin, and analyzed the hydrological response characteristics under different TSCs. The results showed that The SWAT model, driven by CMADS-L40 data, demonstrated robust performance in monthly runoff simulation. The coefficient of determination (R²), Nash–Sutcliffe efficiency coefficient (NSE), and the absolute value of percentage bias (|PBIAS|) during the calibration and validation period all met the accuracy requirements of the model, which validated the applicability of CMADS-L40 data and the SWAT model for runoff simulation at the watershed scale. Changes in territorial spatial patterns are closely correlated with runoff variation. Changes in agricultural production space and forest ecological space show statistically significant negative correlation with runoff change, while industrial production space change exhibits a significant positive correlation with runoff change. The expansion of production space, particularly industrial production space, leads to increased runoff, whereas the enlargement of agricultural production space and forest ecological space can reduce runoff. This article contributes to highlighting the role of land use policy in hydrological regulation, providing a scientific basis for optimizing territorial spatial planning to mitigate flood risks and protect water resources. 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

The ecosystem services (ESs) of forests are the benefits that people derive from forest ecosystems. Their precise recognition is important for differentiating and determining the optimal principles of multifunctional forest management. The aim of this study is to identify some important ESs based on a site classification system at the lowest level—i.e., forest stands, at the forest owner level—as a tool for differentiated management. ESs were assessed within the Czech Republic and are expressed in units in accordance with the very sophisticated Forest Site Classification System. (1) Biomass production: The vertical differentiation of ecological conditions given by vegetation tiers, which reflect the influence of altitude, exposure, and climate, provides a basic overview of biomass production; the highest value is in the fourth vegetation tier, i.e., the Fageta abietis community. Forest stands are able to reach a stock of up to 900–1200 m³·ha⁻¹. The lowest production is found in the eighth vegetation tier, i.e., the Piceeta community, with a wood volume of 150–280 m³·ha⁻¹. (2) Soil conservation function: Geological bedrock, soil characteristics, and the geomorphological shape of the terrain determine which habitats serve a soil conservation function according to forest type sets. (3) The hydricity of the site, depending on the soil type, determines the hydric-water protection function of forest stands. Currently, protective forests occupy 53,629 ha in the Czech Republic; however, two subcategories of protective forests—exceptionally unfavorable locations and natural alpine spruce communities below the forest line—potentially account for 87,578 ha and 15,277 ha, respectively. Forests with an increased soil protection function—a subcategory of special-purpose forests—occupy 133,699 ha. The potential area of soil protection forests could be up to 188,997 ha. Water resource protection zones of the first degree—another subcategory of special-purpose forests—occupy 8092 ha, and there is potentially 289,973 ha of forests serving a water protection function (specifically, a water management function) in the Czech Republic. A separate subcategory of water protection with a bank protection function accounts for 80,529 ha. A completely new approach is presented for practical use by forest owners: based on the characteristics of the habitat, they can obtain information about the fulfillment of the habitat’s ecosystem services and, thus, have basic information for the determination of forest categories and the principles of differentiated management. Full article

Per- and polyfluoroalkyl substances (PFASs) are emerging pollutants of global concern due to their high environmental persistence and bioaccumulative characteristics. This study investigates PFAS concentrations in soils from China through an extensive literature review, covering soil samples from seventeen provinces and the years from 2009 to 2024. It was found that the total concentration of PFAS in soil ranged from 0.25 to 6240 ng/g, with the highest contamination levels observed in coastal provinces, particularly Fujian (620 ng/g) and Guangdong (1090 ng/g). Moreover, Fujian Province ranked the highest among multiple regions with a median PFAS concentration of 15.7 ng/g for individual compounds. Ecological risk assessment, focusing on areas where perfluorooctanoic acid (PFOA) or perfluorooctane sulfonate (PFOS) were identified as the primary soil PFAS compounds, showed moderate ecological risk from PFOA in Shanghai (0.24), while PFOS posed a high ecological risk in Fujian and Guangdong, with risk values of 43.3 and 1.4, respectively. Source analysis revealed that anthropogenic activities, including PFAS production, firefighting foam usage, and landfills, were the primary contributors to soil contamination. Moreover, soil PFASs tend to migrate into groundwater via adsorption and seepage, ultimately entering the human body through bioaccumulation or drinking water, posing health risks. These findings enhance our understanding of PFAS distribution and associated risks in Chinese soils, providing crucial insights for pollution management, source identification, and regulation strategies in diverse areas. Full article