Search Results (9,854)

The large time step (LTS) explicit scheme relaxes the Courant–Friedrichs–Lewy (CFL) restriction by propagating waves across multiple cells per time step and has shown clear efficiency gains for the homogeneous shallow water equations. Earlier Godunov-type LTS constructionscombined an exact Riemann solver with a multi-wave approximation of the rarefaction fan and a random choice method to suppress spurious oscillations. The present work proposes a simpler yet equally accurate variant. The star state is obtained from Toro’s closed-form two-rarefaction approximation (TRA) and then refined by a short Newton iteration; this combination is exact for two-rarefaction configurations, removes the systematic bias of TRA in two-shock configurations, and converges in two to three iterations from the TRA initial guess in all other cases. The rarefaction fan is split into sub-waves with linearly interpolated speeds, and each sub-wave is dispatched to either a left-moving or a right-moving propagator according to the sign of its mean speed. Fractional contributions are resolved based on a deterministic threshold with θ = 0.5. The scheme is validated based on seven one-dimensional flat-bottom Riemann problems covering dry-bed, wet-bed, two-rarefaction, and two-shock configurations, each at CFL numbers 0.9, 3, 8, and 15. The L1 error in water depth remains below 3% for all cases and is as low as 0.2% in the two-shock configuration at CFL = 15. The Xu 2014 dam break is reproduced with an error of 0.4% at CFL = 15 using only three time steps. Full article

The injection of CO₂ into mature natural gas reservoirs is widely recognised for its potential to store carbon dioxide while simultaneously enhancing natural gas recovery. However, across all reservoir pressure and temperature ranges, CO₂ and natural gas are miscible, leading to contamination of the produced gas and increasing surface processing costs. Although miscibility has been a limiting factor in deploying CO₂-EGR-based projects, several strategies have been proposed to mitigate it. In this study, we have analysed the inclusion of water in the CO₂ injection process to reduce mixing, improve natural displacement, and improve carbon dioxide storage security through solubility and residual trapping mechanisms. The simulation was conducted in a 3D reservoir using the CMG-GEM simulator. The results show that the inclusion of water injection improves natural gas recovery by up to 8.04% compared with when only CO₂ was injected. The CO₂ breakthrough time increased by up to 931 days, while the hysteresis and solubility trapped CO₂ were improved by 2.68% and 3.06%, respectively. EGR and CO₂ storage security were found to be affected by reservoir heterogeneity, injection rate, and the perforation depths of injector and producer wells. Full article

Reliable and harmonised soil information remains critically limited across Africa, constraining soil monitoring, climate-resilient agriculture, and evidence-based land management. Existing soil resources are often fragmented, spatially uneven, outdated, or derived from legacy observations, limiting their usefulness for contemporary continental-scale assessment. The Soils4Africa project implemented a coordinated field campaign across 33 African countries between 2022 and 2025 to establish a harmonised soil monitoring framework for agricultural lands. Using a hierarchical probabilistic sampling design, 24,951 soil samples were collected from 14,311 locations, supported by standardised field protocols, digital data capture, QR-based sample traceability, and centralised quality control. This paper presents the conceptual, operational, and data-management framework underpinning the survey and reports baseline field observations on farming systems, land management, vegetation structure, and soil physical constraints. The framework achieved more than 70% of planned sampling coverage despite major logistical, environmental, and security-related constraints. Baseline observations show that African agricultural landscapes remain dominated by smallholder systems, low external input use, limited soil and water conservation, and widespread dependence on rainfed production. Field indicators also reveal sparse woody vegetation cover and common physical constraints, including compaction, coarse fragments, shallow effective rooting depth, and subsoil barriers. Unlike earlier continental resources based largely on legacy profiles or site-based surveillance, Soils4Africa provides a contemporary, harmonised, spatially structured field-survey framework designed to support future laboratory-based soil assessment, digital soil mapping, land suitability analysis, and long-term soil monitoring. The study therefore provides a scalable model for coordinated soil monitoring across diverse African agroecosystems and establishes an operational baseline for subsequent analytical studies. Full article

Sandy desert ecosystems of Central Asia are highly vulnerable to climate change, land degradation, and increasing anthropogenic pressure, yet the soil conditions supporting native desert vegetation remain insufficiently characterized. This study investigates soil development and physicochemical properties under the canopy of Calligonum aphyllum across different geomorphological conditions in the southern Balkhash region of Kazakhstan. Field investigations were conducted within the Ili River delta, where nine soil profiles were described across three geomorphological settings. Soil samples were analyzed using standard soil analytical methods to assess particle-size composition, soil organic matter, nutrient availability, carbonate content, salinity, and sodicity indicators. The studied soils were predominantly sandy, with sand fractions ranging from 88 to 96% and very low clay content, resulting in weak horizon differentiation, high permeability, and limited water-retention capacity. Soil organic matter and total nitrogen contents were consistently low across all sites. Available phosphorus decreased with depth, particularly in carbonate-enriched horizons, whereas exchangeable potassium remained comparatively high. Total salinity was low, with chloride–sulfate and calcium–sodium dominance, and no evidence of sodicity was observed based on SAR values. Clear differences among geomorphological settings were identified, including relatively homogeneous sandy substrates, dust-enriched semi-stabilized sands, and actively reworked aeolian ridges. The results indicate that C. aphyllum can persist under nutrient-poor, coarse-textured sandy conditions and is associated with surface root concentration, local substrate stabilization, and early soil-profile differentiation. These findings highlight the ecological importance of C. aphyllum in sandy desert habitats and provide site-specific soil information relevant to vegetation-based restoration and sustainable land management in arid regions of Central Asia. Full article

Although low-permeability oil reservoirs boast abundant resources, oil recovery remains relatively low due to the limitations of current water flooding development technology in oilfields. To address the current challenges of low-permeability oil reservoirs, nano-SiO₂ particle aqueous solutions, instead of conventional water injection, have been applied to these reservoirs, which can achieve promising results. Nevertheless, due to the simple surface structure of nano-SiO₂ particles, the unsaturated hydroxyl groups on their surfaces tend to undergo electrostatic attraction with cations in formation water, leading to particle aggregation and flocculation, ultimately compromising their stability. Therefore, studying the interaction between nano-SiO₂ particles and cations in saline solutions is of great significance for providing guidance on the application of nano-SiO₂ particles in low-permeability oilfields. In light of this, this paper employs molecular dynamics simulations and quantum chemical methods to investigate the processes of interactions between nano-SiO₂ particles and cations from a microscopic perspective. The results indicate that the interaction zone between monovalent cations and nanoparticles lies approximately 0.2 nm to 0.3 nm away from the particle surface. In comparison, the interaction zone between divalent cations and nanoparticles extends roughly from 0.3 nm to 0.4 nm from the particle surface. The range and depth of influence of divalent cations are more pronounced. No covalent or ionic bonds are formed between monovalent cations and nanoparticles. However, divalent cations can form ionic bonds with nanoparticles, thereby altering their structural configuration. Among these interactions, electrostatic forces represent the dominant interaction force responsible for changing the configuration of nano-SiO₂ particles, whereas van der Waals forces and hydrogen bonding forces are merely weak interactions. Moreover, as the valence state of the cation increases from monovalent to divalent, the cation forms new ionic bonds with the nano-SiO₂ particles, significantly modifying their structural configuration and further undermining their stability. The findings of this study can improve our understanding of the existing state of nano-SiO₂ particles in formation water, which can help to improve the application effect of nano-SiO₂ particles in low-permeability oil fields. Full article

Semi-arid wetlands are highly sensitive to changes in hydrological regimes, as strong evaporation often exceeds limited natural recharge. Ecological water replenishment is widely used to restore these systems, but schemes designed only to meet water-volume targets may cause excessive hydrodynamic disturbance, promote sediment resuspension, and increase the release of internal pollutants. In this study, we developed an ecological water-replenishment assessment framework for Chahannaoer Wetland that incorporates ecological water-demand thresholds, suspended-solids disturbance, and an AHP–entropy weight–TOPSIS decision model. Using hydrological and meteorological data from 2014 to 2024, six replenishment scenarios were evaluated in terms of water-balance recovery, disturbance control, and habitat suitability. The results show that Chahannaoer Wetland experienced a persistent evaporation-dominated water deficit. The mean annual natural recharge was 0.225 × 10⁸ m³, with a mean annual ecological water shortage of 1.03 × 10⁸ m³ and an evapotranspiration-to-recharge ratio of 3.42–4.56. Based on the previous comprehensive water-quality assessment using DO, COD, NH₃-N, TN, and TP, the minimum water volume required to maintain Class IV water quality was 0.86 × 10⁸ m³, whereas the suitable ecological water demand ranged from 1.27 × 10⁸ to 1.56 × 10⁸ m³. With the total replenishment volume held constant, centralized replenishment met the required water volume but substantially increased near-bed disturbance and sediment resuspension risk. By contrast, decentralized uniform replenishment performed best, with the highest relative closeness coefficient of 0.9105, a disturbance index of approximately 0.32, and water depths maintained within the suitable habitat range of 30–50 cm. These findings suggest that ecological restoration in semi-arid wetlands should move beyond volume-based water supplementation and pay greater attention to the timing, pathway, and hydrodynamic effects of replenishment. The proposed framework provides a quantitative basis for optimizing ecological water replenishment in evaporation-dominated wetlands and other inland lakes in arid and semi-arid regions. Full article

Against the background of global warming, snow cover, as an extremely sensitive and active component of the cryosphere, plays an indispensable role in regulating regional water circulation, energy balance mechanisms and the climate system. To explore the dynamic variation characteristics and driving mechanisms of snow depth in southeastern Xizang, this study took Chamdo City as the research area. Based on multi-source datasets including snow depth, meteorology, vegetation, topography, and population density from 2000 to 2020, methods such as the coefficient of variation, Theil–Sen trend analysis, Mann–Kendall test, Hurst index, and geographical detector were adopted to systematically analyze the spatiotemporal patterns of snow depth variations and their influencing factors. The results indicate that, temporally, the overall snow depth in Chamdo City showed a fluctuating increasing trend over the past 20 years, with an annual growth rate of 0.03 cm. It exhibited distinct characteristics across three stages: snow depth increased at a rate of 0.12 cm·a⁻¹ from 2000 to 2005, decreased at 0.05 cm·a⁻¹ during 2005–2015, and rose rapidly from 2015 to 2020 at a growth rate of 0.52 cm·a⁻¹. Spatially, the distribution of snow depth varied significantly. The extremely shallow snow cover area (≤2 cm) accounted for 51.71% of the total area, primarily concentrated in low-altitude regions with intensive human activities. In contrast, the relatively deep (6–10 cm) and extremely deep (>10 cm) snow cover areas together constituted 14.34% of the total, mainly distributed in high-altitude regions with sparse populations. Hurst index analysis revealed that 61.71% of the study area exhibited persistent changes in snow depth, with a trend toward deepening snow cover in the future. The results from the geographical detector show that air temperature (X9, q = 0.90) was the core driving factor dominating the static spatial differentiation of multi-year average snow depth. Furthermore, the interactions between slope (X4) and air temperature (X9), vegetation type (X6) and air temperature (X9), and population density (X5) and aspect (X8) all demonstrated bivariate enhancement effects, with explanatory power significantly higher than that of individual factors. This study provides a scientific reference for water resource management, snowmelt runoff prediction and snow disaster prevention in Chamdo City. Full article

Addressing the severe risks of floor instability and leakage in underground coal mine reservoirs in Western China under coupled mining and hydraulic pressures, this study developed a fully coupled stress-damage-seepage numerical model. Incorporating rock heterogeneity based on the geological conditions of the Shendong mining area, the model systematically simulates the evolution of floor damage under varying storage pressures, burial depths, mining heights, and lithologies. The simulation results demonstrate that storage pressure is the primary driver for deep damage propagation via a “hydraulic wedging” mechanism, governed by a critical activation threshold of 1.0 MPa. Specifically, before the water storage pressure reaches 1.0 MPa, the floor damage remains dormant and basically unchanged, stagnating at a shallow level. However, once the pressure exceeds this 1.0 MPa threshold, it overcomes the effective confining stress, abruptly shifting the failure mode from shallow discrete fracturing to deep penetrating failure, which is accompanied by an order-of-magnitude surge in permeability. Furthermore, a dimensionless sensitivity analysis reveals that burial depth and lithology strongly govern the failure path and depth. Notably, mudstone possesses a significantly lower intrinsic permeability, and even when subjected to damage, its water barrier performance remains superior to that of sandstone because its localized plastic shear characteristics highly restrict permeability mutations. In contrast, brittle sandstone is highly susceptible to tensile cracking and the formation of deep penetrating seepage channels. Additionally, mining height demonstrates weak sensitivity to the depth of floor damage due to an “equivalent unloading” mechanism, which validates the technical feasibility of constructing underground water reservoirs in ultra-thick coal seams. These findings provide a vital theoretical foundation for the scientific site selection of underground reservoirs and the precise determination of operational water level thresholds to ensure long-term stability. Full article

This work introduces a Targeted Emulsified-Solvent Injection (TESI) process for extracting bitumen from oil sands. In TESI, a solvent is emulsified near the emulsion phase inversion point (PIP), where the interfacial tension and the emulsion stability are very low. This allows the solvent to be easily emulsified and then deposited onto the bitumen-coated porous media (under lower shear conditions, where the emulsion breaks), mixing with bitumen, decreasing bitumen viscosity, and enabling mobilization and diluted bitumen recovery. The design of the surfactant-solvent formulation was guided by the Hydrophilic-Lipophilic-Difference and Net-Average-Curvature (HLD-NAC) frameworks. The HLD-NAC was used to identify a formulation with less than 1% surfactant exhibiting ultralow interfacial tension (~10⁻³ mJ/m²), at the PIP, where HLD = 0. This formulation was injected into columns packed with bitumen-coated sands at varying salinities and water-to-solvent ratios. Using optimal conditions, bitumen recoveries of up to 83% can be obtained at room temperature, without the need for steam or high-pressure injection, a condition suitable for intermediate-depth reservoirs. The effluent emulsion of diluted bitumen can be gravity-separated, allowing for the recycling of the aqueous solution containing the surfactant. The recovery curves were modeled using a continuous stirred tank reactor (CSTR) model coupled with a Capillary number model for thin viscous films that allowed the prediction of effluent diluted bitumen viscosities and an estimation of the pressure drops in the column that were consistent with experimental observations. Full article

Hydrological processes in dryland urban lakes are jointly shaped by landscape pattern dynamics and water resource scarcity, yet the spatial correspondence between landscape fragmentation and lake ecological water demand remains poorly understood. This study took Yuehai Lake, a typical dryland urban lake in Northwest China, as a case study. Landscape pattern analysis was integrated with a water balance model to quantify ecological water demand and its spatial correspondence with landscape metrics. The model coupled the Penman–Monteith equation, a depth-modified evaporation model, and a Darcy’s Law-based zonal seepage calculation. Results showed that: (1) the landscape structure remained highly stable over 2014–2022, with the Aggregation Index ranging from 95.07% to 95.28% and the Largest Patch Index from 90.20% to 90.70%; (2) the annual ecological water demand for maintaining ecosystem integrity was estimated at 2036.97 × 10⁴ m³, comprising inherent lake water volume of 1138.02 × 10⁴ m³ (55.9%), evapotranspiration of 659.72 × 10⁴ m³ (32.4%), and lakebed seepage of 239.23 × 10⁴ m³ (11.7%); and (3) evapotranspiration was concentrated between May and August, accounting for 80.5% of annual losses, with water surface evaporation dominating the flux at 91.5%. These findings suggest a spatial correspondence between landscape metrics and ecological water demand components, providing quantitative support for differentiated water supplementation strategies in dryland urban lakes. Full article

Plateau valley cities are increasingly exposed to flood risk because topographic constraints, ecological fragility, and rapid urbanization jointly intensify runoff sensitivity. Although dynamic and process-based assessments of flood regulation service (FRS) have advanced, limited attention has been given to how changes in urban green space (UGS) components are associated with marginal runoff-retention responses in a plateau valley setting. Taking central Lhasa as a case, this study combined Sentinel-2-based UGS mapping, intPLUS land-use scenario simulation, Soil and Water Assessment Tool (SWAT) runoff modeling, XGBoost, SHapley Additive exPlanations (SHAP), and accumulated local effects (ALE) to evaluate the FRS responses under multiple scenarios. A pressure–response overlay was further used to diagnose spatial mismatches between runoff pressure and modeled regulation response. Results showed that UGS expanded by 5212.66 ha from 2017 to 2025, indicating a marked greening trend, but the natural development scenario projected a 1403.80 ha decline by 2033. In contrast, the ecological protection scenario projected a 915.98 ha increase and produced a stronger modeled runoff-retention response, although the improvement remained spatially uneven across subbasins. Model-based interpretation identified forest land as the most influential predictor of runoff-depth-based FRS response, while grassland, park green space, and waterfront green space were generally associated with runoff-depth reduction and showed distinct nonlinear response patterns. Specifically, forest land and grassland showed diminishing marginal effects after higher increment ranges, park green space exhibited delayed effectiveness before clearer regulation benefits emerged, and waterfront green space reached effective response ranges at relatively low proportional increments. Spatial diagnosis further showed that 19 subbasins, accounting for 18.88% of the study area, remained response-lagged, mainly along urban expansion fringes where runoff pressure was not matched by sufficient modeled regulation response. The integrated framework provides a transferable, spatially explainable basis for plateau valley FRS assessment, whereas the identified thresholds and zoning implications remain case-specific and require local validation. Full article

Ground penetrating radar (GPR) is widely used for non−destructive evaluation of pavement structures, yet the automatic detection of internal cracks remains challenging due to variations in crack geometry, infilling materials, and antenna configurations that significantly alter signal responses. Most existing machine learning approaches focus on improving detection accuracy but pay limited attention to the inherent symmetries and invariances present in GPR data. This study proposes a symmetry−informed learning framework for robust pavement crack detection across different antenna orientations and material conditions. Laboratory concrete slabs containing cracks with varying widths (2–30 mm) and depths (10–110 mm) were constructed and tested under five representative crack states: air−filled, dry sand, fresh water, saturated sand, and bitumen−filled. GPR data were collected using a 2.3 GHz system under perpendicular and parallel broadside antenna orientations to capture rotational variability. A deep learning model was developed with symmetry−aware training strategies that exploit rotational consistency and material−invariant feature learning. Comparative experiments were conducted to evaluate detection performance and cross−condition generalization. Results demonstrate that incorporating symmetry improves model robustness and generalization across unseen orientations and filling conditions. The proposed framework highlights the importance of symmetry−informed learning for reliable AI−driven GPR inspection of pavement infrastructure. Full article

Groundwater is a critical water source in the semi-arid West Liao River Basin (WLRB). Based on daily observations from 117 monitoring wells distributed across the basin during 2019–2024, this study analyzed interannual and seasonal groundwater-level dynamics and identified areas of relative groundwater stress using groundwater level elevation (WLE) and depth to water (DTW). The Mann–Kendall test, Sen’s slope estimator, ordinary kriging, and a composite risk index were applied to quantify temporal trends, map spatial patterns, and classify groundwater risk. Regional WLE showed weak interannual variability but a distinct seasonal cycle, with positive anomalies from January to April and negative anomalies from June to September. At the well scale, 51 wells (43.59%) exhibited significant increases, whereas 36 wells (30.77%) showed significant decreases. Sen’s slope ranged from −2.75 to 0.61 m/year, indicating that the strongest local changes were associated with groundwater-level decline. Spatially, WLE was generally higher in the southwest and lower toward the northeast. Areas with WLE decline were concentrated in the central-western and southern sectors, whereas relative WLE increases occurred in parts of the northern and eastern sectors. The low-, medium-, and high-risk classes included 39, 38, and 39 wells, accounting for 33.62%, 32.76%, and 33.62% of the wells retained for the risk assessment, respectively. High-risk wells clustered in the central-western and southern areas, while low-risk wells dominated the northern and eastern sectors. These results highlight the importance of well-scale monitoring for identifying priority areas of groundwater stress. The proposed framework provides a practical basis for screening priority monitoring areas and supporting spatially differentiated groundwater management in semi-arid basins. However, this study is limited by the relatively short monitoring period (2019–2024) and the lack of quantitative driver attribution; therefore, the findings reflect recent groundwater dynamics rather than long-term secular trends. Full article

Straw blind ditch is an ecological subsurface drainage technology with potential application value for the improvement of saline–alkali land. However, straw blind ditch burial depth is a key design parameter that directly affects drainage, salt leaching, and nutrient regulation. In this study, field experiments were conducted in 2024 and 2025 to evaluate the effects of different straw blind ditch burial depths on soil water content and temperature, soil salinity, nitrate nitrogen (NO₃⁻-N), ammonium nitrogen (NH₄⁺-N), and available phosphorus (Olsen-P) in coastal saline–alkali soil. The experiment was arranged in a randomized complete block design (RCBD) with three replicates and included three straw blind ditch burial depths, 60 cm (SD60), 45 cm (SD45), and 30 cm (SD30), with no blind ditch as the control (CK). Across the 0–60 cm soil profile and the two growing seasons, SD60 reduced mean soil electrical conductivity (EC) by 48.9% compared with CK, while SD45 and SD30 reduced mean soil EC by 30.0% and 30.5%, respectively. In the 0–10 cm surface soil layer, the EC reduction under SD60 reached 50.4%. Straw blind ditch burial depth also markedly enhanced soil nitrogen and phosphorus availability. Across the 0–60 cm soil profile, soil NO₃⁻-N under SD60, SD45, and SD30 increased by 26.0%, 18.0%, and 24.6%, respectively, compared with CK. The SD60 treatment exhibited the highest profile-averaged soil NH₄⁺-N, with an increase of approximately 46.6% compared with CK. In addition, SD60 and SD45 increased profile-averaged soil Olsen-P by 60.4% and 64.3%, respectively, relative to CK. Overall, SD60 provided the most balanced improvement in soil salinity reduction and nitrogen availability, whereas SD45 showed the greatest enhancement of Olsen-P. These findings suggest that optimizing straw blind ditch burial depth can improve soil salinity and nutrient status in coastal saline–alkali soil. Full article

The rapid growth of electric mobility, renewable-energy storage, and portable electronics has sharply increased global lithium demand. Conventional lithium extraction methods, including hard-rock mining and brine evaporation, are land-intensive, slow, water-consumptive, and carbon-intensive. Adsorption has therefore received substantial attention for lithium recovery, due to its simple operation, cost-effectiveness, and facile scalability. In this regard, zeolite-based adsorbents have emerged as promising next-generation materials, mainly because of their crystalline frameworks, tunable pore architectures, ion-exchange functionality, and exceptional thermal and chemical stability. Existing reviews on adsorption-based lithium recovery have predominantly focused on polymeric materials, ion-exchange resins, and lithium-ion sieves (including lithium manganese oxide-based, titanium-based, and aluminum hydroxide-based adsorbents). To fill this gap, we present a dedicated and comprehensive review of zeolite-based adsorbents for sustainable lithium recovery from non-conventional lithium resources such as brines, geothermal fluids, seawaters, and battery-recycling leachates. By systematically and rigorously analyzing existing studies on this topic, we identify five guiding design principles: (i) zeolite framework charge density, (ii) zeolite framework topology and pore architecture (iii) morphology (size and shape), (iv) zeolite-based hybrid materials, and (v) operational design parameters (e.g., pH and temperature). Each design element is discussed in depth to clarify how lithium adsorption capacity and selectivity, transport behavior, and adsorption mechanisms can be controlled across diverse feedstocks. We further discuss the advantages, limitations, and future research needs for zeolite-based lithium capture. To the best of our knowledge, this is the first review centered on zeolite-based materials for lithium recovery. The knowledge and insights provided here aim to drive researchers into advancing zeolite-based adsorbents toward sustainable, next-generation lithium recovery technologies. Full article