Search Results (2,833)

In arid open-pit mines, rainfall-triggered slope instability presents significant risks, but quantitative thresholds are poorly defined due to limited integration of transient seepage and stability in low-permeability soils. This study fills this gap by using GeoStudio’s SEEP/W and SLOPE/W modules to simulate rainfall effects on a moderately steep-slope (51° average) limestone mine slope in Ningxia’s Kazimiao Mining Area (annual precipitation: 181.1 mm). The novelty lies in identifying a 12 h saturation window under intense rainfall (≥100 mm h⁻¹), during which pore water pressure stabilizes as soil reaches saturation, creating an “infiltration buffering effect” driven by arid soil properties (hydraulic conductivity: 2.12 × 10⁻⁴ cm s⁻¹). Results show that the factor of safety (FOS) drops sharply within 12 h (e.g., from 1.614 naturally to 1.010 at 200 mm h⁻¹) and then stabilizes, with FOS remaining >1.05 (basically stable) under rainfall intensities ≤ 50 mm h⁻¹, but drops into the less-stable range (1.00–1.05) at 100–200 mm h⁻¹, reaching marginal stability (FOS ≈ 0.98–1.02) after 24 h of extreme events, according to GB/T 32864-2016. Slope protection measures increase FOS (e.g., 2.518 naturally). These findings quantify higher instability thresholds in arid compared to humid regions, supporting regional guidelines and informing early-warning systems amid climate-related extremes. This framework enhances sustainable slope management for mines worldwide in arid–semi-arid zones. Full article

Invasive species are a recurring global problem, and the water hyacinth (Pontederia crassipes) is a well-known example. Various strategies have been explored to manage its spread, including its use as an agricultural amendment. However, when P. crassipes biomass is incorporated into soil and undergoes degradation, it may increase soil conductivity and promote metal leaching, potentially affecting soil biota, particularly microbiota. Saprophytic fungi play a key role in the decomposition and renewal of organic matter, and their resilience to stressors is crucial for maintaining soil function. Thus, the aim of this study was to evaluate the effects of P. crassipes biomass extracts on the saprophytic fungus Trametes versicolor by evaluating fungal growth and metabolic changes [including sugar content, phosphatase enzymatic activity, and reactive oxygen species (ROS) production]. The fungus was exposed for 8 days to a dilution series of extracts (100%—undiluted, to 3.13%) prepared from P. crassipes biomass collected at five locations in Portuguese wetlands. Two sites were in the south, within a Mediterranean climate (Sorraia and Estação Experimental António Teixeira), and three were in the north, within an Atlantic climate (São João de Loure, Pateira de Fermentelos, and Vila Valente), representing both agricultural-runoff–impacted areas and recreational zones. Extracts were used to simulate a worst-case scenario. All extracts have shown high conductivity (≥15.4 mS/cm), and several elements have shown a high soluble fraction (e.g., K, P, As, or Ba), indicating substantial leaching from the biomass to the extracts. Despite this, T. versicolor growth rates were generally not inhibited, except for exposure to the São João de Loure extract, where an EC₅₀ of 45.3% (extract dilution) was determined and a significant sugar content decrease was observed at extract concentrations ≥25%. Possibly due to the high phosphorous leachability, both acid and alkaline phosphatase activities increased significantly at the highest percentages tested (50% and 100%). Furthermore, ROS levels increased with increasing extract concentrations, yet marginal changes were observed in growth rates, suggesting that T. versicolor may efficiently regulate its intracellular redox balance under stress conditions. Overall, these findings indicate that the degradation of P. crassipes biomass in soils, while altering chemical properties and releasing soluble elements, may not impair and could even boost microbiota, namely saprophytic fungi. This resilience highlights the potential ecological benefit of saprophytic fungi in accelerating the decomposition of invasive plant residues and contribution to soil nutrient cycling and ecosystem recovery. Full article

Karst ground collapses triggered by groundwater fluctuations pose a significant threat to the safety and stability of tunnel engineering. In this study, taking the Yakouzai Tunnel as a case, a combination of physical model tests and numerical simulations was employed to investigate the mechanisms of groundwater-induced karst collapse. A self-designed physical model device reproduced the full process of soil cavity initiation, expansion, and roof failure. Numerical simulations were further conducted to analyze the evolution of pore water pressure, stress distribution, and displacement under both groundwater drawdown and rise conditions. The results indicate that concentrated seepage erosion at the cavity arch foot is the primary driver of cavity initiation, with cyclic suffusion promoting its progressive expansion. Rapid groundwater drawdown generates vacuum suction that markedly reduces roof stability and may induce sudden collapse, whereas groundwater rise, although providing partial support to the roof, intensifies shear stress concentration and leaves the cavity in an unstable state. The findings highlight that karst collapse is governed by the coupled effects of seepage erosion, arching degradation, differential settlement, and vacuum suction, providing a scientific basis for monitoring, prediction, and mitigation of karst hazards. Full article

The ramifications of climate change, which are projected to lead to increased drought, desertification, and water scarcity, are expected to have a significant impact on the agricultural sector of Türkiye, particularly in the Mediterranean coastal regions. This study presents an extensive evaluation of potential agricultural drought conditions in southwestern Türkiye, using a high-resolution, convection-permitting (0.025°) modeling approach. We employ a single, physically consistent model chain, dynamically downscaling the CMIP6 MPI-ESM-HR Earth System Model with the COSMO-CLM regional climate model at a convection-permitting (CP) resolution (0.025°) under IPCC Shared Socioeconomic Pathways SSP3-7.0, reflecting a high-emission scenario with regional socioeconomic challenges. Southwestern Türkiye, situated at the intersection of the Mediterranean and continental climates, hosts rare climatic and ecological conditions that sustain a highly productive and diverse agricultural system. This region forms the backbone of Türkiye’s agricultural economy but is increasingly vulnerable to climate variability and fluctuations that threaten its agricultural stability and resilience. Our study employs a novel approach that utilizes multivariate assessment of agricultural drought in the Mediterranean Region by integrating precipitation, soil moisture, and temperature variables from 2.5 km resolution climate simulations. Agricultural drought conditions were evaluated using the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSI), and the Standardized Temperature Index (STI), derived by normalizing respective climate variables from climate simulations spanning from 1995 to 2014 for the historical period, from 2040 to 2049 and from 2070 to 2079 for future projections. CP climate simulations (CPCSs) exhibit a modest warm and dry bias during all seasons but slightly wetter conditions during summer when compared with station observations. Correlations between indices indicate that soil moisture variations in the future will become more sensitive to changes in temperature rather than precipitation. Results from this specific model chain reveal that the probability of compound events where precipitation and soil moisture deficits coincide with anomalously high temperatures will rise for all threshold levels under the SSP3-7.0 scenario towards the end of the century. For the most severe conditions (|Z| > 1.2), the compound likelihood increases to about 3%, highlighting the enhanced occurrence of rare events in a changing climate. These findings, conditional on the model and scenario used, provide a high-resolution, physically grounded perspective on the potential intensification of agricultural drought regimes. Full article

Glyphosate is the most widely used herbicide in the world for weed control; however, due to lixiviation, wind and runoff effects, an important fraction can reach the soil, aquifers and surface waters, affecting environmental and human health. The behavior of glyphosate in two agricultural soils (C1: silty clay texture, and C2: silty loam texture) was analyzed in this study using a laboratory-scale model. Water transfer was modeled with the Richards equation, while glyphosate transport was modeled using the advection–dispersion equation, with both solved using finite difference methods. The glyphosate dispersion coefficient was obtained from laboratory concentration data derived from the soil profile via inverse modeling using a non-linear optimization algorithm. The goals of this study were to (i) quantify glyphosate retention in soils with different physical and chemical properties, (ii) calibrate a numerical model for the estimation of dispersivity and simulation of short- and long-term scenarios, and (iii) assess vulnerability to groundwater contamination. The results showed that C1 retained a greater amount of glyphosate in the soil profile, while C2 was considered more vulnerable as it liberated the contaminant more easily. The model accurately reproduced the measured concentrations, as evidenced by the RMSE and R² statistics, thus supporting further scenario simulations allowing for prediction of the fate of the herbicide in soils. The approach utilized in this study may be useful as a tool for authorities in environmental fields, enabling better control and monitoring of soil contamination. These findings highlight potential risks of contamination and reinforce the importance of agricultural management strategies. Full article

Leakage from defective buried pipelines can lead to progressive soil erosion and void formation, ultimately resulting in ground collapse or sinkhole development. To better understand the underlying mechanisms of this process, this research utilizes a coupled computational fluid dynamics (CFD)–discrete element method (DEM) modeling approach to investigate soil erosion processes driven by water leakage from defective underground pipelines. The numerical model captures fluid–particle interactions at both macroscopic and microscopic scales, providing detailed insights into erosion initiation, void zone evolution, and particle transport dynamics under varying hydraulic and geometric conditions. Parametric studies were conducted to evaluate the effects of exfiltration pressure, defect size, and particle diameter on erosion behavior. Results show that erosion intensity and particle migration increase with hydraulic pressure up to a threshold, beyond which compaction and particle bridging reduce sustained transport. The intermediate defect size (12.7 mm) consistently produced the most continuous and stable erosion channels, while smaller and larger defects exhibited localized or asymmetric detachment patterns. Particle size strongly influenced erosion susceptibility, with finer grains mobilized more readily under the same flow conditions. The CFD–DEM simulations successfully reproduce the nonlinear and self-reinforcing nature of internal erosion, revealing how hydraulic gradients and particle rearrangement govern the transition from local detachment to large-scale cavity development. These findings advance the understanding of subsurface instability mechanisms around leaking pipelines and provide a physically consistent CFD–DEM framework that aligns well with published studies. The model effectively reproduces the key stages of erosion observed in the literature, offering a valuable tool for assessing erosion-induced risks and for designing preventive measures to protect buried infrastructure. Full article

In recent years, the public environmental protection consciousness has improved regarding the source of drinking water. However, the risk status and sources of heavy metals (HMs) in the soil around drinking water sources remain unclear. The typical Drawdown Zone (DZ) of Danjiangkou Reservoir is taken as an example in this study. Pollution levels of HMs and associated ecological and human health risks were evaluated under four land-use types during the low-water-level period. The sources of 10 HMs were determined using the positive matrix factorization (PMF) model and correlation analysis. Quantitative source-oriented risk identification was then conducted by integrating risk characteristics with source apportionment. The results indicate that soils in the study area are generally slightly polluted, with comprehensive potential ecological risks at a medium level. Farmland soils exhibit the highest pollution and ecological risk levels, particularly for Hg and Cd. Our Monte Carlo simulation-based human health risk assessment shows that, compared with non-carcinogenic risks, carcinogenic risks should be given further attention. Farmland poses higher health risks than other land-use types, and children are more vulnerable than adults. Four main sources were identified: transportation sources (29.5%), agricultural activities (32%), natural sources (19.3%), and atmospheric deposition (19.2%). The source-oriented risk assessment indicates that agricultural activities are the priority control source for ecological risks (64.7%), with Hg as the primary control element. Transportation and agricultural sources are the primary contributors to carcinogenic risks in children (57.1%) and adults (57.1%), with Ni as the primary control element. Full article

Climate change and water scarcity are major threats to the sustainability of wheat production in Mediterranean regions. Thus, timely and reliable water demand assessments are crucial to drive decisions on crop management strategies that are useful for agricultural adaptation to climate change challenges. Although the AquaCrop model is widely used to infer crop yields, it requires continuous field-based observations (mainly soil water content and crop coverage). Often, these areas suffer from a scarcity of in situ data, suggesting the need for remote sensing and model-based decision support. In this framework, this research intends to compare the performance of the AquaCrop model using four different input combinations, with one employing ERA5-Land and crop cover retrieved by satellite images exclusively. A field experiment was conducted on durum wheat (highly sensitive to water stress and playing a strategic role in national food security) in northwest Tunisia during the growing season of 2024–2025, where meteorological variables, green Canopy Cover (gCC), Soil Water Content (SWC), and final yields (biological and grain) were monitored. The AquaCrop model was applied. Four model input combinations were evaluated. In situ meteorological data or ERA5-Land (E5L) reanalysis were combined with either measured-gCC (measured-gCC) or Sentinel-2 NDVI-derived gCC (NDVI-gCC). The results showed that E5L reproduced temperature with RMSE < 2.4 °C (NSE > 0.72) and ETo with RMSE equal to 0.57 mm d⁻¹ (NSE = 0.79), while precipitation presented larger discrepancies (RMSE = 4.14 mm d⁻¹, NSE = 0.58). Sentinel-2 effectively captured gCC dynamics (RMSE = 15.65%, NSE = 0.73) and improved AquaCrop perfomance (RMSE = 5.29%, NSE = 0.93). Across all combinations, AquaCrop reproduced yields within acceptable deviations. The simulated biological yield ranged from 9.7 to 11.0 t ha⁻¹ compared to the observed 10.3 t ha⁻¹, while grain yield ranged from 3.0 to 3.5 t ha⁻¹ against the observed 3.3 t ha⁻¹. As expected, the best agreement with measured yield data was obtained using in situ meteorological data and measured-gCC, even if the use of in situ meteorological data coupled with NDVI-gCC, or E5L-based meteorological data coupled with NDVI-gCC, produced realistic estimates. These results highlight that the application of AquaCrop employing E5L and Sentinel-2 inputs is a feasible alternative for crop monitoring in data-scarce environments. Full article

The 17 November 2023 M_W 6.8 earthquake located offshore of Southern Mindanao, Philippines, triggered soil liquefaction along the lowlands of the Sarangani Peninsula. Detailed mapping, geomorphological interpretations, geophysical surveys, comparison with predictive models, and grain size analysis were conducted to obtain a comprehensive understanding of the earthquake parameters and subsurface conditions that permitted liquefaction. Soil liquefaction manifested as sediment and water vents, fissures, lateral spreads, and ground deformation, mainly along landforms with shallow groundwater levels such as river deltas, fills, floodplains, and beaches. In populated areas, ground failure due to liquefaction also damaged some buildings. All these impacts fall within the boundaries of the available liquefaction hazard maps for Sarangani Peninsula and the predictive empirical equations generated by various authors. Simulated peak ground acceleration values also indicate that sufficient ground shaking was generated for the soil to liquefy. Refraction microtremor (ReMi) surveys reveal shear wave velocities ranging from 121 to 215 m/s, which infer the presence of soft and stiff soils beneath the surface, promoting the sites’ potential to liquefy. Grain size analyses of sediment ejecta confirm the presence of these liquefiable sediments from the subsurface, with grain sizes ranging from silt to medium sand. The results of three-component microtremor (3CMt) surveys also show varying sediment thicknesses, which are consistent with the thickness of soft sediment layers inferred by ReMi surveys. The information resulting from this study may be useful for researchers, planners, and engineers for liquefaction hazard assessment and mitigation, especially in the Sarangani Peninsula. Full article

This study investigated the mechanical properties of a boltless hexagonal segment lining structure in TBM tunnels through a 1:10 scale similarity model test. The analysis considered the effects of burial depth and lateral pressure coefficient. A gypsum-diatomite composite simulated C50 concrete segments, and a custom loading system applied equivalent soil-water loads. The tests examined variations in bending moment, axial force and displacement. The results demonstrate that: (1) The tongue-and-groove joints behave like hinges, effectively reducing joint bending moments. (2) The unique staggered interlocking structure induces significantly higher axial forces at the joints than traditional rectangular segments, increasing susceptibility to stress concentration. (3) Increased burial depth has the most significant impact on the tunnel crown, where the bending moment, axial force, and displacement change most notably. (4) The lateral pressure coefficient (λ) alters the joint load transfer mechanism by modifying the structure’s triaxial stress state. An optimal λ of 0.6 maximizes axial force transfer efficiency, while excessively high values impair horizontal load-bearing capacity. (5) Structural failure was ductile, with a final ovality slightly exceeding 10‰. The findings of this study can provide a reference for the design and application of similar boltless hexagonal segment tunnels. Full article

Nickel contamination poses a serious risk to ecosystems and human health. Phytoremediation provides a sustainable solution. This study evaluates the ability of Helinathus annuus L. to tolerate and accumulate nickel under simulated Mediterranean and semi-arid conditions, representing a short-term contamination event with nickel-enriched irrigation. Laboratory experiments assessed growth, tolerance, and Ni distribution within plant tissues. Results showed that Ni uptake increased with concentration, mainly in roots, while translocation to aerial parts remained limited. The bioconcentration factors ranged from 1.32 to 2.55, and the translocation factors from 0.46 to 0.60, indicating efficient uptake but restricted metal mobility. Higher water availability enhanced Ni absorption, suggesting that soil moisture facilitates metal transport and root activity. Helinathus annuus L. demonstrated good tolerance at moderate Ni levels but reduced growth and accumulation efficiency at higher concentrations, confirming its potential for phytostabilization in Mediterranean soils affected by metal contamination. Full article

The hydrological processes of red soil slope farmland are complex, and the vertical migration of nitrogen (N) is influenced by these processes, which present different layering characteristics of water flow. Previous studies on the vertically stratified transport of N on slope soils have mainly relied on rainfall simulation, lacking a comprehensive study of the overall process of N leaching from surface soil to underground under natural conditions. To investigate the impact of these hydrological processes on the transport of N at different layers under natural rainfall events, large-scale field runoff plots were constructed as draining lysimeters to conduct a consecutive 2-year observation experiment at Jiangxi Soil and Water Conservation Ecological Science and Technology Experimental Station, China. The runoff (the water of 0 cm), interflow, deep percolation, soil moisture content (SMC), total nitrogen (TN), nitrate nitrogen (NO₃⁻-N) and ammonium nitrogen (NH₄⁺-N) concentrations were monitored and determined. The N loss of red soil farmland under two treatments, namely grass mulching (FC, a coverage of 100% with Bahia grass) and exposed treatment (BL, without anything covered), were measured. The relationships between hydrological factors and different forms of N losses were analyzed. The results indicate the following: (1) Deep percolation is the main pathway of water loss and N loss for red soil slope farmland, accounting for over 85% of the total water loss and N Loss. Grass mulching can significantly reduce surface runoff and N loss. (2) Vertically stratified N is mainly NO₃⁻-N, and the concentrations of each form of N show the same trend: deep percolation > interflow > runoff. (3) Water loss, rainfall, and SMC are closely related to the stratified loss of N, with correlation coefficients ranging from 0.74 to 0.98. The correlation analysis and redundancy analysis (RDA) on the relationships between different forms of N losses and hydrological factors indicate that rainfall was the primary factor driving the stratified loss of N in red soil slope farmland. Full article

Soil salinization poses a major threat to agricultural sustainability in arid regions worldwide, where it is intrinsically linked to irrigated agriculture. In these water-scarce environments, the equilibrium of the water and salt balance is easily disrupted, causing salts to accumulate in the root zone and directly constraining crop growth, thereby creating an urgent need for precise water and salt management strategies. While precise water and salt transport models are essential for prediction and control, their accuracy is often compromised by parameter uncertainty. To address this, we developed a lumped water–salt balance model for the Hetao Irrigation District (HID) in China, integrating farmland and non-farmland areas and vertically structured into root zone, transition layer, and aquifer. A novel calibration approach, combining random sampling with Kernel Density Estimation (KDE), was introduced to identify optimal parameter ranges rather than single values, thereby enhancing model robustness. The model was calibrated and validated using data from the Yichang sub-district. Results showed that the water balance module performed satisfactorily in simulating groundwater depth (R² = 0.79 for calibration, 0.65 for validation). The salt balance module effectively replicated the general trends of soil salinity dynamics, albeit with lower R² values, which reflects the challenges of high spatial variability and data scarcity. This method innovatively addresses the common challenge of parameter uncertainty in the model, narrows the parameter value ranges, enhances model reliability, and incorporates sensitivity analysis (SA) to identify key parameters in the water–salt model. This study not only provides a practical tool for managing water and salt dynamics in HID but also offers a methodological reference for addressing parameter uncertainty in hydrological modeling of other data-scarce regions. Full article

With advancements in solar-induced fluorescence (SIF) observation technology and the evolution of vegetation radiative transfer models, SIF signals can now be more effectively interpreted and leveraged from a mechanistic perspective. This, in turn, facilitates a deeper understanding of the mechanistic link between SIF and photosynthesis. Considering the impact of water stress on terrestrial ecosystems, this paper simulated SIF and gross primary productivity (GPP) values using the STEMMUS-SCOPE model at half-hour scales from 2017 to 2023 at the Daman site. The simulation results were compared and validated against flux tower observations and SCOPE model outputs. Taking advantage of irrigation events in the semi-arid irrigated farmland, we assessed the accuracy of STEMMUS-SCOPE in simulating SIF and GPP under drought stress, as well as its capability to quantitatively analyze the impacts of water stress on SIF and GPP. The results show that the accuracy of the SIF and GPP values simulated by the STEMMUS-SCOPE model is higher than that of the SCOPE model. The averaged R² and RMSE between the SIF simulated by STEMMUS-SCOPE model and the observed SIF values are 0.66 and 0.29 mW m⁻² nm⁻¹, and the averaged R² and RMSE between the GPP simulated by the STEMMUS-SCOPE model and the observed GPP values from 2017 to 2023 are 0.88 and 4.93 µmol CO₂ m⁻² s⁻¹, respectively. Especially under relatively drought conditions, the R² between the SIF simulated values and observed values is 0.84, and the R² between the GPP simulated values and observed values is 0.96. By further combining soil moisture content (SMC) and canopy conductance (Gs) analyses, we found that the response of the STEMMUS-SCOPE simulations under water stress was consistent with previous findings on the impacts of water deficits, thereby confirming the model’s reliability for drought conditions. Under drought stress, the decline in fluorescence emission efficiency (ΦF) with decreasing Gs and SMC was smaller than that of the light use efficiency (LUE). Therefore, the STEMMUS-SCOPE model is promising for investigating the SIF–GPP relationship under drought stress. Full article

Partially frozen soil (PFS) is comprises of coexisting unfrozen water and ice within its pores at subzero temperatures. The review paper examines how unfrozen water content (UWC) and pore ice content interact during phase changes under near-freezing conditions, governed by microscopic thermodynamic equilibrium. Key theories describing why UWC persists (premelting, disjoining pressure) and the soil freezing characteristic curve (SFCC), along with measurement techniques, including the gravimetric approach to advanced nuclear magnetic resonance for characterization of water content. The influence of the water–ice phase composition on mechanical behavior is discussed, signifying pore pressure and effective stress. Various modelling approaches categorized into empirical SFCC, physio-empirical estimations, and emerging machine learning and molecular simulations are evaluated for capturing predictions in PFS behavior. The relevance of PFS to infrastructure foundation, tailings dams, permafrost slope stability, and climate change impacts on cold regions’ environmental geotechnics is also highlighted as a challenges in practical application. Hence, understanding pore pressure dynamics and effective stress in PFS is critical when assessing frost heave, thaw weakening, and the overall performance of geotechnical structures in cold regions. By combining micro-scale phase interaction mechanisms and macro-scale engineering observations, this review paper provides a theoretical understanding of the underlying concepts vital for future research and practical engineering in cold regions. Full article