Search Results (779)

Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and soil properties on water infiltration in a high-Andean environment. A double-ring infiltrometer, the Water Drop Penetration Time (WDPT, s) method, and laboratory physicochemical characterization were employed. Soils under forest cover exhibited significantly higher quasi-steady infiltration rates (i_s, 0.248 ± 0.028 cm·min⁻¹) compared to grazing areas (0.051 ± 0.016 cm·min⁻¹) and agricultural lands (0.032 ± 0.013 cm·min⁻¹). Soil organic matter content was positively correlated with i_s. The modified Kostiakov infiltration model provided the best overall fit, while the Horton model better described infiltration rates approaching i_s. Sand and clay fractions, along with K⁺, Ca²⁺, and Mg²⁺, were particularly significant during the soil’s wet stages. In drier stages, increased Na⁺ concentrations and decreased silt content were associated with higher water repellency. Based on WDPT, agricultural soils exhibited persistent hydrophilic behavior even after drying (median [IQR] from 0.61 [0.38] s to 1.24 [0.46] s), whereas forest (from 2.84 [3.73] s to 3.53 [24.17] s) and grazing soils (from 4.37 [1.95] s to 19.83 [109.33] s) transitioned to weakly or moderately hydrophobic patterns. These findings demonstrate that native Andean forest soils exhibit a higher infiltration capacity than soils under anthropogenic management (agriculture and grazing), highlighting the need to conserve and restore native vegetation cover to strengthen water resilience and mitigate the impacts of land-use change. Full article

In this study, to solidify the silt in an expressway, a stabilizing agent composed of industrial wastes, such as ordinary Portland cement (OPC), calcium based alkaline activator (CAA), silicate solid waste material (SISWM) and sulfate solid waste material (SUSWM) was developed. Orthogonal experiments and comparative experiments were carried out to analyze the strength and water stability of the stabilized silt, and get the optimal proportion of each component in the stabilizing agent. A series of laboratory tests, including unconfined compressive strength (UCS), water stability (WS), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD) analyses, were conducted on solidified silt samples treated with the stabilizing agent at optimal mixing ratios of OPC, CAA, SISWM, and SUSWM to elucidate the evolution of mineral composition and microstructure. Full article

Urban parks are an integral component of cities; however, they are susceptible to heavy metal contamination from anthropogenic sources. Here, we investigated the moss Pleurozium schreberi and tree leaves as bioindicators for monitoring heavy metal contamination in urban parks. We determined heavy metal concentrations in P. schreberi, leaf tissues of selected tree species, and soil samples collected from various locations within a designated urban parks. The order of heavy metal accumulation was Zn > Pb > Cr > Cu > Ni > Cd > Hg in soil and Zn > Cu > Pb > Cr > Ni > Cd > Hg in P. schreberi. The order was Zn > Cu > Cr > Ni > Pb > Cd > Hg in linden and sycamore leaves, while birch leaves displayed a similar order but with slightly more Ni than Cr. The heavy metal concentration in the tested soils correlated positively with finer textures (clay and silt) and negatively with sand. The highest metal accumulation index (MAI) was noted in birch and P. schreberi, corresponding to the highest total heavy metal accumulation. The bioconcentration factor (BAF) was also higher in P. schreberi, indicating a greater ability to accumulate heavy metals than tree leaves, except silver birch for Zn in one of the parks. Silver birch displayed the highest phytoremediation capacity among the analysed tree species, highlighting its potential as a suitable bioindicator in heavy metal-laden urban parks. Our findings revealed significant variation in heavy metal accumulation, highlighting the potential of these bioindicators to map contamination patterns. Full article

The implantable capsule grouting pile is a novel pile foundation technology in which a capsule is affixed to the side of the implanted pile to facilitate grouting and achieve extrusion-based reinforcement. This technique is designed to improve the bearing capacity of implanted piles in coastal areas with deep, soft soil. This study conducted model tests involving multiple grouting positions across different foundation types to refine the construction process and validate the enhancement of bearing capacity. Systematic measurements and quantitative analyses were performed to evaluate the earth pressure distribution around the pile, the resistance characteristics of the pile end, the evolution of side friction resistance, and the overall bearing performance. Special attention was given to variations in the lateral friction resistance adjustment coefficient under different working conditions. Furthermore, an actual case analysis was conducted based on typical soft soil geological conditions. The results indicated that the post-grouting process formed a dense soil ring through the expansion and extrusion of the capsule, resulting in increased soil strength around the pile due to increased lateral earth pressure. Compared to conventional piles, the grouted piles exhibited a synergistic improvement characterized by reduced pile end resistance, enhanced side friction resistance, and improved overall bearing capacity. The ultimate bearing capacity of model piles at different grouting depths across different foundation types increased by 6.8–22.3% compared with that of ordinary piles. In silty clay and clayey silt foundations, the adjustment coefficient η_s of lateral friction resistance of post-grouting piles ranged from 1.097 to 1.318 and increased with grouting depth. The findings contribute to the development of green pile foundation technology in coastal areas. Full article

Soil aggregates play critical roles in regulating the behavior of heavy metal in soils. To understand the distribution of cadmium (Cd) in aggregates of different soil types, as well as their roles in regulating the Cd bioavailability of bulk soils, four major arable soils, including acidic, neutral, and calcareous purple soils and calcareous yellow soil (APS, NPS, CPS, and CYS), were sampled from Chongqing, China, for aggregate separation and determination of the total Cd(T-Cd) distribution, fractionation, and extractability in various-sized aggregates. A pot experiment with ryegrass (Lolium perenne L.) was conducted to evaluate the Cd bioavailability in bulk soils as influenced by aggregates. The results show that the composition of soil aggregates varies a lot among soils: lower soil pH tends to increase the proportion of macroaggregates while decreasing that of smaller aggregates. The Cd distribution, HCl-extractability, and active fraction (AF, T-Cd/HCl-Cd) in aggregates are all soil type-dependent, with pH and particle size being the main determining factors; the distribution pattern of Cd concentrated in smaller aggregates is only found for CPS and CYS (pH > 7.5) upon exogenous Cd addition, though the finest aggregates (silt–clay, <0.053 mm) consistently exhibited the highest Cd enrichment for all tested soils. The Cd extractability and AF values in all aggregates show a sequence of APS > NPS > CPS > CYS, indicating the fundamental influence of soil pH on Cd availability. Higher AF values over bulk soils, either in silt–clay aggregates or in microaggregates (0.053–0.25 mm), whereas lower AF in macroaggregates (1–2 mm) are found for APS and NPS, which correspond to the relative portions of Ex-Cd and Fe/Mn oxide-bound Cd (Fe/Mn-Cd) in these aggregates. In contrast, less variation of AF values among aggregates is observed for CPS and CYS and for APS/NPS upon Cd addition. Pot experiments demonstrated strong positive correlations between ryegrass Cd uptake and HCl-Cd in silt–clay aggregates and T-Cd in microaggregates, while a negative correlation was observed with T-Cd in macroaggregates. These findings supply new insight into the mechanisms of aggregates in controlling Cd bioavailability in bulk soils and shed light on the development of new strategies for remediating Cd-polluted soils. Full article

An increasing number of soils, including those in EU countries, are affected by organic matter deficiency and the deterioration of nutrients, and using mineral fertilizers is often associated with negative environmental impacts. One of the basic recommendations for sustainable agriculture is to increase the proportion of organic fertilizers in crop production and preserve soil biodiversity. An increasingly common organic fertilizer is biogas plant digestate, the physical and chemical properties of which depend primarily on the waste material used in biogas production. However, the fertilizer value of this additive and its effects on the soil environment, including beneficial organisms, remain insufficiently studied. Soil macrofauna, particularly earthworms, play a crucial role in soil ecosystems, because they significantly impact the presence of plant nutrients, actively participate in forming soil structures, and strongly influence organic matter dynamics. The present study was undertaken to determine the effects of fertilizing a silt loam soil with the solid fraction of digestate in monoculture crop production on earthworm community characteristics and the resulting changes in selected soil physicochemical properties. The research was conducted at a single site, so the original soil characteristics across the experimental plots were identical. Plots were treated annually (for 3 years; 2021–2023) with different levels of digestate: DG100 (100% of the recommended rate; 30 t ha⁻¹), DG75 (75% of the recommended rate; 22.5 t ha⁻¹), DG50 (15 t ha⁻¹), DG25 (7.5 t ha⁻¹), and CL (a control plot without fertilizer). An electrical method was used to extract earthworms. Those found at the study site belonged to seven species representing three ecological groups: Dendrodrilus rubidus (Sav.), Lumbricus rubellus (Hoff.), and Dendrobaena octaedra (Sav.) (epigeics); Aporrectodea caliginosa (Sav.), Aporrectodea rosea (Sav.), and Octolasion lacteum (Örley) (endogeics); and Lumbricus terrestris (L.) (anecics). Significant differences in the abundance and biomass of earthworms were found between the higher level treatments (DG100, DG75, and DG50), and the lowest level of fertilization and the control plot (DG25 and CL). The DG25 and CL plots showed an average of 24.7% lower earthworm abundance and 22.8% lower biomass than the other plots. There were no significant differences in the earthworm metrics between the plots within each of the two groups (DG100, DG75, and DG50; and DG25 and CL). The most significant influence on the average abundance and average biomass of Lumbricidae was probably exerted by soil moisture and the annual dosage of digestate. A significant increase in the abundance and biomass of Lumbricidae was shown at plots DG100, DG75, and DG50 in the three successive years of the experiment. The different fertilizer treatments were found to have different effects on selected soil parameters. No significant differences were found among the values of the analyzed soil traits within each plot in the successive years of the study. Full article

Mycorrhizal symbiosis in rice enhances drought adaptation but there are limited studies regarding the frequency and amplitude of mycorrhizae colonization in traditional landraces. This study investigates mycorrhizal colonization frequency (FMS) and intensity (IRS) in 12 rice landraces across three agroecological zones (Tarai, Inner-Tarai, Mid-hill) of Far-West Nepal under drought stress. Field experiments exposed landraces to control, intermittent, and complete drought treatments, with soil properties and root colonization analyzed. Results revealed FMS and IRS variations driven by soil composition and genotype. Mid-hill soils (acidic, high organic matter) showed lower FMS but elevated IRS under drought, while neutral pH in Tarai and silt/clay-rich soils supported higher FMS. Sandy soil in Inner-Tarai also promoted FMS. Drought significantly increased IRS, particularly in Anjana and Sauthiyari (Tarai), Chiudi and Shanti (Inner-Tarai), and Chamade and Jhumke (Mid-hill), which exhibited IRS surges of 171–388%. These landraces demonstrated symbiotic resilience, linking mycorrhizal networks to enhanced nutrient/water uptake. Soil organic matter and nutrient levels amplified IRS responses, underscoring fertility’s role in adaptation. FMS ranged from 50 to 100%, and IRS 1.20–19.74%, with intensity being a stronger drought-tolerance indicator than frequency. The study highlights the conservation urgency for these landraces, as traditional varieties decline due to hybrid adoption. Their drought-inducible mycorrhizal symbiosis offers a sustainable strategy for climate-resilient rice production, emphasizing soil–genotype interactions in agroecological adaptation. Full article

Visible and near-infrared (Vis–NIR) spectroscopy enables the rapid prediction of soil properties but faces three limitations with conventional machine learning: information loss and overfitting from high-dimensional spectral features; inadequate modeling of nonlinear soil–spectra relationships; and failure to integrate multi-scale spatial features. To address these challenges, we propose ReSE-AP Net, a multi-scale attention residual network with spatial pyramid pooling. Built on convolutional residual blocks, the model incorporates a squeeze-and-excitation channel attention mechanism to recalibrate feature weights and an atrous spatial pyramid pooling (ASPP) module to extract multi-resolution spectral features. This architecture synergistically represents weak absorption peaks (400–1000 nm) and broad spectral bands (1000–2500 nm), overcoming single-scale modeling limitations. Validation on the LUCAS2009 dataset demonstrated that ReSE-AP Net outperformed conventional machine learning by improving the R² by 2.8–36.5% and reducing the RMSE by 14.2–69.2%. Compared with existing deep learning methods, it increased the R² by 0.4–25.5% for clay, silt, sand, organic carbon, calcium carbonate, and phosphorus predictions, and decreased the RMSE by 0.7–39.0%. Our contributions include statistical analysis of LUCAS2009 spectra, identification of conventional method limitations, development of the ReSE-AP Net model, ablation studies, and comprehensive comparisons with alternative approaches. Full article

Because the loess widely used in the channel water conservancy projects in the Loess Plateau has a loose structure, low mechanical strength, and is prone to collapse when immersed in water, its comprehensive properties, such as structural strength and water resistance, must be greatly improved. Based on our previous work on the modification of Aga soil in Tibet, China, this study added hydrophobic n-dodecyltrimethoxysilane (WD10) to water glass solution (the main components are potassium silicate (K₂SiO₃) and silicic acid (H₂SiO₃) gel, referred to as PS) to obtain a composite coating PS-WD10, which was sprayed on the surface of loess blocks to achieve a full consolidation effect. We not only systematically investigated the morphology, chemical composition, and consolidation mechanism of the composite coating but also conducted in-depth and detailed research on its application performance such as friction resistance (structural strength), hydrophobicity, resistance to pure water and salt water immersion, and resistance to freeze–thaw cycles. The results showed that the PS-WD10 composite coating had better consolidation performance for loess blocks than the single coating of PS solution and WD10. For the loess block samples coated with the composite coatings, after 50 friction cycles, the weight loss rate was less than 15 wt%, and the water contact angle was above 120°. The main reason is that the good permeability of the PS solution and the excellent hydrophobicity of WD10 produce a good synergistic effect. The loess blocks coated with this composite coating are expected to replace traditional functional materials for water conservancy projects, such as cement and lime, in silt dam water conservancy projects, and also have better environmental protection and sustainability. Full article

This investigation proposes an effective protocol (cutting) for Paulownia tomentosa production in Tunisia during the 2022–2024 period. The effects of the three interactive parameters: root cutting diameter (L1, 0.5; L2, 0.8; L3, 1.25; and L4, 2 cm), indole-3-butyric acid (IBA) hormone concentrations (C, 0; T1, 0.1%; and T2, 0.3%), and soil type (S1: 50% silt + 50% potting soil, and S2: 43% potting soil + 43% silt + 14% sand), were investigated. The data showed that cutting roots with 0.5 cm dimensions, a cutting treatment with hormone (0.3%), and the S2 soil type corresponded to a growth enhancement in height. These results revealed the broad changes in flowering of P. tomentosa. Also, data revealed that the root cutting diameter had the greatest influence on the biochemical contents of 4-month-old P. tomentosa sprouts. The studied pathway revealed that the auxin precursor IBA contributes toward active auxin [indole-3-acetic acid (IAA)] biosynthesis. Overall, this study found substantial changes in the morphological, biochemical, and floral features of new P. tomentosa sprouts under the interactive factors. To summarize, vegetative propagation of Paulownia, particularly through root cutting, allows for proliferation and plantation development. These findings can be applied to future breeding efforts with Paulownia to improve and protect it as a woody species, forage, and medicinal plant. Full article

The formation of soil cracks in soil slopes can compromise structural integrity. Guar gum, as a natural high-molecular-weight biopolymer, offers environmental and economic advantages in soil stabilizers due to its biodegradability, strong binding properties, and ability to form a three-dimensional network structure. To investigate its improvement effects, outdoor dry shrinkage cracking tests were conducted on silt loam using different guar gum dosages. Image preprocessing was performed using Photoshop software, and Python algorithms combined with the PCAS system were employed to quantitatively analyze the development process of cracks, revealing the evolution patterns of basic crack parameters, fractal dimensions, and probability entropy. The results indicate the following: (1) the addition of guar gum improves the water retention capacity of the soil, with the average moisture content of the samples decreasing as the guar gum content increases; (2) as the guar gum content increased, the total length, total area, and surface crack ratio of the cracks all increased, but the average crack width decreased significantly, with the maximum decrease reaching 9.8%, indicating that guar gum can effectively suppress the expansion of crack width and slow down the infiltration rate of rainwater; (3) the fractal dimension of crack area is less affected by guar gum content, while the fractal dimension of crack length is significantly influenced by guar gum content. Combining both parameters can effectively characterize crack morphology and distribution. The final fractal dimension of crack length generally ranges from 1.2 to 1.3, while the fractal dimension of the crack area remains stable between 1.55 and 1.65; (4) the addition of guar gum has a minor effect on the probability entropy of cracks, with a change of less than 3%, indicating that it does not significantly influence the randomness of cracks. Therefore, this study confirms that guar gum has a significant effect in controlling crack width and optimizing the uniformity of the crack network. Through its mechanisms of binding soil particles and delaying drying shrinkage, it provides an important reference for the ecological protection of cohesive soil slopes. Full article

Soil texture, defined by the proportions of sand, silt, and clay particles in the soil, is one of the most essential physical properties of soil. High-resolution soil texture data can provide critical parameter support for soil hydrological modeling, agricultural production management, and ecosystem assessment. In digital soil mapping, previous studies often predicted the sand, silt, and clay contents in soil and then indirectly calculated soil texture. Currently, approaches that directly map soil texture by classification modeling are gaining increasing attention due to the decreased error from data conversion, but few studies have systematically compared these two methods yet. In this study, we comprehensively assessed the performance of direct and indirect predicting soil texture using four machine learning algorithms (e.g., extreme gradient boosting, random forest, gradient boosting decision tree, and extremely randomized tree) with 190 covariates from the Digital Elevation Model, Sentinel-1/2 satellite images, and classification maps and generated a 10 m resolution soil texture map based on 405 topsoil (0–20 cm) sample data collected in Suichuan County, China. The results showed that compared with indirect predictions, direct predictions improved overall accuracy (OA) by 20.57–44.19% and the Kappa coefficient (Kappa) by 0.220–0.402. Among the models used, the XGB model achieved the highest accuracy (OA: 0.948; Kappa: 0.931) and the lowest uncertainty (confusion index: 0.052). The direct prediction map (nine classes recorded) exhibited more detailed and diverse spatial distribution patterns than the indirect prediction map (six classes recorded), aligning better with the actual environment. Based on accuracy validation and spatial distribution, the performance of the XGB model was best during direct prediction. The Shapley additive explanation from the XGB model revealed that the normalized height and stream power indices were the most significant factors driving the soil texture in the study area. Our results provide a reference for future studies on soil texture mapping using machine learning models. Full article

Delineating soil management zones in cocoa cultivation areas can help optimize production and minimize ecological and environmental risks. This research assessed the spatial distribution of heavy metal concentration and soil fertility indicators in Cross River State, Nigeria, to delineate soil management zones (MZs). A total of n = 63 georeferenced, composite soil samples were collected at the 0–30 cm depth increment, air-dried, and subjected to physicochemical analysis. The soil data were subjected to principal component analysis (PCA), and the selected principal components (PCs) were used for fuzzy c-means clustering analysis to delineate the MZs. The result indicated that soil pH varied from 4.8 (strongly acidic) to 6.3 (slightly acidic), with high average organic carbon contents. The degree of contamination was low, while the ecological risk indicator (RI) of the environment under cocoa cultivation ranged from low risk (RI = 18.24) to moderate risk (RI = 287.15), with moderate risk areas mostly found in patches around the central and upper regions. Higher pH was associated with increased levels of exchangeable Ca, Mg, and K, and TN and OC. Strong spatial dependence was observed for silt, pH, OC, Mg, Zn, Cu, Pb, Cd, Cr, and DC. The result showed the first six principal components (PCs) with eigenvalues >1 accounting for 83.33% of the cumulative variance, and three MZs were derived via the selected six PCs using fuzzy c-means clustering analysis. The results of this study further indicated that MZ3 had the highest pH (6.06), TN (0.24%), OC (2.79%), exchangeable Ca (10.62 cmol/kg), Mg (4.01 cmol/kg), and K (0.12 cmol/kg). These were significantly (p < 0.05) higher than those observed in MZ2 and MZ1, and they represent the most fertile parts of the study area. Furthermore, 40.6% of the study area had marginal soil (i.e., soil under MZ2). Full article

This paper presents the physical, hydrogeological, and geochemical characterizations of two types of tailings: one from the nickel–cobalt (Ni–Co) and the other from the lead–zinc (Pb–Zn) industries. The study is restricted only to Ni and Zn ions behavior. The mineralogical composition of the studied tailings is primarily composed of oxides and hydroxides of iron, aluminum, and silica. Based on their grain size, these wastes are geotechnically classified as low plasticity silts, with permeability ranging from 10⁻⁸ m/s to less than 10⁻⁹ m/s. Batch and column flow tests, along with metal transport tests using heavy metal-contaminated wastewater, reveal that these tailings have an adsorption capacity for metals such as nickel (Ni) and zinc (Zn) ranging from 2000 to 6000 mg/kg of solid. This high adsorption capacity surpasses that of many clayey soils used for sealing municipal, industrial, mining, and metallurgical waste deposits. Additionally, these wastes can neutralize the acidity of wastewater. The results indicate that the mineralogical composition and pH of these tailings are key factors determining their adsorption characteristics and mechanisms. Due to their characteristics, these tailings could be evaluated for use as low-permeability reactive geochemical barriers (LPRGB) in the conditioning of repositories for the storage of industrial, urban, mining and metallurgical waste. This would allow large volumes of tailings to be repurposed effectively. Full article

This study explored the enzymatic formation of gel-like polymeric matrices through carbonate precipitation for dust suppression in Yellow River silt. The hydrogel-modified EICP method effectively enhanced the compressive strength and resistance to wind–rain erosion by forming a reinforced bio-cemented crust. The optimal cementation solution, consisting of urea and CaCl₂ at equimolar concentrations of 1.25 mol/L, was applied to improve CaCO₃ precipitation uniformity. A spraying volume of 4 L/m² (first urea-CaCl₂ solution, followed by urease solution) yielded a 14.9 mm thick hybrid gel-CaCO₃ crust with compressive strength exceeding 752 kPa. SEM analysis confirmed the synergistic interaction between CaCO₃ crystals and the gel matrix, where the hydrogel network acted as a nucleation template, enhancing crystal bridging and pore-filling efficiency. XRD analysis further supported the formation of a stable gel-CaCO₃ composite structure, which exhibited superior resistance to wind–rain erosion and mechanical wear. These findings suggest that gel-enhanced EICP represents a novel bio-gel composite technology for sustainable dust mitigation in silt soils. Full article