Search Results (288)

Tunnels excavated in non-coal oil- and gas-bearing strata may experience the seepage and intermittent ingress of an oil–gas–water mixture during construction, creating aggressive corrosive conditions that can compromise the integrity of primary support and the safety margin of the final lining. However, the coupled degradation mechanism of primary support and its cascading effect on lining safety under such conditions remain poorly understood. Based on the Huaying Mountain Tunnel project, this study investigates the corrosion-driven damage evolution of primary support and its implications for the structural safety of the secondary lining under wet–dry cycling exposure. Accelerated wet–dry cycling tests were performed on concrete specimens using an on-site crude-oil–formation-water mixture collected during tunnelling, with exposure levels ranging from 0 to 120 cycles. Laboratory observations were then combined with inverse identification of degradation-dependent material parameters to establish a corrosion-informed mechanical description, which was implemented in numerical simulations for structural response assessment. Results show a staged evolution of mechanical properties, with an initial increase followed by progressive deterioration. After 120 cycles, compressive strength, tensile strength, and elastic modulus decreased by approximately 18.9%, 23.1%, and 17.4%, respectively. Degradation is more pronounced in the corroded zone, with tensile capacity and stiffness deteriorating earlier than compressive resistance. Numerical results indicate that corrosion leads to significant stress redistribution and damage development. The sidewall tensile stress reaches 2.80 MPa after 120 cycles, exceeding the post-corrosion capacity, while the safety factor drops below the code threshold at 90 cycles. The overall safety probability decreases from 1.0 to 0.4, accompanied by a degradation in safety grade from Level I to Level IV. These findings provide a quantitative basis for deterioration assessment, safety verification, and maintenance planning for tunnels subjected to oil–gas corrosive environments. Full article

Durability of clay-based mixes is often considered a limitation for their use in modern construction projects, especially in those involving additive manufacturing techniques. This study focuses on developing sustainable extrudable cob mixes and investigating the effect of sand particle grading, curing regime and mix composition on compressive strength, flexural strength, stress–strain response, capillary water absorption, wetting-drying cycles effect, and abrasion resistance. Results showed a significant positive impact of fine-sized sand addition into the mix on the mechanical strength and durability, due to better compaction and denser final cob mixes. Extending oven curing improves the compressive and flexural strength of all mixes due to the accelerated strength development from the higher temperature exposure. Lastly, the addition of high clay content allows for improving the compressive and flexural strength at prolonged curing aging under normal air-drying conditions. These mixes also exhibit low water absorption. Conversely, results revealed that the lime content plays a crucial role in reducing surface wear, with lime-rich mixes exhibiting lower erosion rates than the other mixes. Lime-stabilized cob mixes also demonstrate improved durability under cyclic wetting and drying. Full article

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviors were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades. Full article

Persistent droughts and shifting precipitation regimes continue to threaten water security across the United States, with arid and semi-arid regions remaining the most vulnerable. This study examines the spatial and temporal patterns of aridity and water scarcity across drought-prone stations (111) and regions of the U.S. using 30 years (1991–2020) of precipitation records from xmACIS II. Weather stations were categorized into arid (<10 inches/year), semi-arid (10–20 inches/year), and non-arid (>20 inches/year) zones, revealing a distinct west–east gradient: arid and semi-arid conditions prevail across the western and central U.S., while the eastern regions remain largely non-arid. Drought frequency analysis spanning 2000–2019 indicates that certain regions experienced exceptional drought conditions (D3 or higher) for more than 50% of the study period, with localized areas enduring over 300 weeks of extreme drought. Long-term precipitation trends (1920–2020) in Texas, Washington, and South Dakota reflect a modest increase in precipitation; however, CMIP6 multi-model ensemble projections under a 2 °C and 4 °C warming scenario point to divergent future trajectories, with some regions experiencing increased wetness while others face progressive drying. These findings offer actionable insights for drought monitoring and climate adaptation strategies, underscoring the heightened vulnerability of arid and semi-arid zones to intensify water scarcity. Full article

Climate change is expected to impact rainfall amount, seasonality, and dry/wet patterns, with direct implications for rainwater harvesting systems. This study aims to quantify how future rainfall may affect rainwater harvesting systems across Brazil by combining multi-model climate projections with a daily water balance model. A single-family social housing archetype (60 m² roof area; four occupants; 150 L/day/person; non-potable demand equal to 30% of total demand) was simulated for 652 Brazilian cities, using bias-corrected daily rainfall from the CLIMBra dataset and nineteen climate models. Historical conditions were compared with near-future and far-future projections under the SSP2-4.5 and SSP5-8.5 scenarios. Historically, the greater potential for potable water savings has occurred in wetter, less seasonal climates, such as those in the North. In contrast, more seasonal and drought-prone areas, such as the Northeast, showed lower reliability. In future climates, most models indicate relative reductions in the potential for potable water savings in the North, Northeast, and Centre–West, with larger reductions under SSP5-8.5 and in the far-future scenarios. The South shows the most significant divergence between models and may increase the potential for potable water savings in some projections. On the other hand, in the South, the volume of rainwater harvesting system overflow increases under future scenarios. This work contributes to the literature by delivering a national-scale, multi-model, uncertainty-aware evaluation of rainwater harvesting performance under non-stationary rainfall regimes. Full article

Under the combined effects of climate change and anthropogenic activities, the dry–wet pattern of the Yellow River Basin is undergoing substantial reconfiguration, yet its long-term evolution and driving mechanisms remain unclear. This study constructs a Terrestrial Water Storage Anomaly-based Drought Severity Index (TWSA-DSI) using 1995–2014 as the historical period to characterize spatiotemporal dry–wet heterogeneity. Future changes during 2026–2100 are projected for the near future (2026–2060) and far future (2061–2100) under the SSP126, SSP245, and SSP585 scenarios. A comprehensive driving factor system incorporating vegetation cover, land use, meteorological conditions, and socio-economic factors is established, and dominance analysis is applied to quantify the controlling mechanisms of terrestrial water storage change (TWSC). Results indicate that the basin experienced a historical transition from aridification to humidification. Future dry–wet conditions differ markedly from the historical period, with the basin shifting toward overall humidification as emissions increase. The driving mechanisms of aridification and humidification are significantly different and precipitation is the decisive driving factor influencing the dry–wet evolution of the Yellow River Basin. Especially in the far future under the SSP585 scenario, the proportion of precipitation is as high as 54.9%. These findings provide scientific support for sustainable water-resource management under climate change. Full article

The Upper Colorado River Basin (UCRB), through the process of snow accumulation, to snowmelt, to streamflow runoff, provides a critical water source to approximately 40 million residents in the Southwestern United States. Given the importance of late fall–winter–early spring (October, November, December, January, February, March, or ONDJFM), cumulative precipitation, future estimates of ONDJFM cumulative precipitation, and potential drought occurrence would provide a benefit to water managers and planners. Previous research efforts successfully reconstructed (extended the period of record) the regional April 1st Snow Water Equivalent (SWE) in the UCRB using tree-ring chronologies and reconstructed climate (El Niño–Southern Oscillation or ENSO). The current research efforts differ by (a) incorporating future [Shared Socioeconomic Pathway (SSP) 5-8.5] predictions of ONDJFM cumulative precipitation (in lieu of April 1st SWE) at a single station location (Kendall R.S.) in the UCRB; (b) reconstructing ONDJFM cumulative precipitation (in lieu of April 1st SWE) using tree-ring chronologies and ENSO; and (c) evaluating an alternative reconstructed ENSO index. The reconstructed record, recent past observations, and future (SSP 5-8.5) ONDJFM cumulative precipitation were then combined to provide a paleo perspective of future drought. Results indicate that extreme ONDJFM cumulative precipitation drought periods projected for the ~2040s were exceeded in the reconstructed record. A pattern of alternating wet and dry conditions was also identified, consisting of a wet (pluvial) period in the 2030s, followed by drought conditions in the 2040s, and another wet period in the 2050s. Many of the extreme future wet (pluvial) periods exceeded those in the recent record and reconstructed record. Full article

In highway widening projects, the wet–dry cycling effect of weakly expansive soil fill under seasonal groundwater fluctuations exacerbates differential settlement. This study establishes a three-dimensional numerical model for a widened road with weakly expansive soil, based on a redeveloped numerical method and actual engineering projects. Through multi-scenario numerical simulations, the influence patterns and weighting factors of widening methods, road height, and water level on differential settlement were clarified. Three safety levels for differential settlement were defined using 6 cm and 12 cm as thresholds. A prediction model based on support vector machines was established to determine the combined threshold limits of key parameters under different differential settlement boundaries. The control effectiveness of sand replacement, water-blocking layers, and wicking geotextiles was comparatively evaluated: sand replacement reduces differential settlement by approximately 70% on average and is applicable to all scenarios; water-blocking layers reduce settlement by about 50% and are more suitable for bilateral widening or unilateral widening of low embankments; wicking geotextiles are unsuitable for controlling differential settlement in high-water-level areas. Selection principles for control methods under different conditions were proposed based on engineering requirements, and field tests validated the effectiveness of the proposed solutions. Full article

Grasslands, covering over 40% of terrestrial land surfaces, play a critical role in regional water cycling through their greening processes. However, the decoupling mechanisms between grassland greening and water availability (WA) changes across the Northern Hemisphere, along with their future trajectories, remain poorly understood. Here, we integrated multi-source satellite observations with CMIP6 model ensembles to systematically assess the spatiotemporal evolution and trend divergence of leaf area index (LAI) and WA across Northern Hemisphere grasslands from 2000 to 2100. Our results showed that grassland LAI exhibited sustained growth during 2000–2020, with 55.28% of regions showing significant increasing trends. However, 73.67% of grassland regions experienced declining WA during the historical period, revealing widespread decoupling between grassland greening and water deficit. Future scenario projections indicated a reversal to increasing WA trends, with 57.51% of regions showing significant increases under SSP5–8.5. Furthermore, 61.87% of grasslands exhibited greening-driven drying (GDD) characteristics during the historical period, while greening-driven wetting (GDW) regions were projected to expand to 72.44% in the future. Analysis along aridity gradients revealed that humid zones contributed most prominently to LAI and WA changes. Mechanistic decomposition demonstrated that grassland WA changes shifted from precipitation-dominated control (53.60%) in the historical period toward a regime jointly governed by precipitation dominance and coupled precipitation–evapotranspiration drivers in the future. Concurrently, the dominant factor controlling grassland greening transitioned from vapor-pressure deficit (VPD) to temperature (TEM) control. Additionally, driving factors exhibited pronounced differentiation patterns along aridity gradients during the historical phase: arid zones were dominated by soil moisture (SM) and semi-arid zones displayed dual control by SM and VPD, while humid zones were governed by coupled TEM-VPD regulation. This study reveals the divergent trends between grassland greening and WA and unravels their driving mechanisms, offering important scientific evidence for formulating regionally differentiated ecological water resource management strategies. Full article

In the long-term operation of canals in loess areas, instability and landslides frequently occur due to the effect of wetting–drying cycles, which severely restricts the long-term safe operation of engineering projects. To reveal the evolution law of loess strength under wetting–drying cycles and establish a strength prediction model, this study conducted wetting–drying cycle tests and direct shear tests, analyzing the effects of different cycle times, dry densities, and initial water contents on the shear strength and its parameters. A combined model of improved adaptive genetic algorithm and backpropagation neural network (IAGA-BP) was adopted for shear strength prediction. An adaptive crossover and mutation operator based on the Sigmoid function, which combines the fitness value with the population iteration number, was proposed. By optimizing the parent selection strategy and the uniform crossover genetic method, the population diversity was effectively maintained, and premature convergence was avoided. The test results show that with the increase in the wetting–drying cycle times, both the shear strength and strength parameters of loess exhibit a trend of gradual attenuation and eventually tend to be stable. The increase in the dry density and initial water content can reduce the degradation amplitude of soil cohesion after five wetting–drying cycles. The model verification results indicate that all evaluation indicators of the IAGA-BP neural network model (MAPE = 3.75%, MAE = 0.95 kPa, MSE = 9 × 10⁻⁴, R² = 0.975) are significantly superior to those of the traditional BP and GA-BP models, with the comprehensive prediction performance improved by 62% and 46%, respectively. This model not only effectively overcomes the defect that traditional models are prone to fall into local extremum but also shows significant advantages in prediction accuracy and convergence speed. This study can provide a theoretical reference for the calculation of loess strength degradation and the prediction of long-term stability under the environment of wetting–drying alternation. Full article

Drought is expected to intensify under climate change, posing significant risks to Mediterranean agroecosystems. This study provides long-term projections of drought and wetness conditions for three representative Mediterranean regions—Eastern Mancha (Spain), Sidi Bouzid Governorate (Tunisia), and the Beqaa Valley (Lebanon)—to support climate-resilient planning. Future monthly precipitation (2020–2050) was dynamically downscaled using the Weather Research and Forecasting (WRF) model under the RCP4.5 scenario, and the Standardized Precipitation Index (SPI12) was subsequently applied to quantify drought severity at annual and monthly scales. By integrating dynamically downscaled WRF projections with pixel-based SPI analysis across three spatially distinct Mediterranean regions, the study provides a novel, spatially explicit and comparative framework for assessing future drought and wetness extremes in support of climate-resilient planning. The results reveal spatial variability and moderate temporal fluctuations across the three regions, reflected in differing timings and intensities of their driest and wettest hydrological years. Spain is projected to experience its driest hydrological year in 2046–2047, Tunisia in 2030–2031, and Lebanon in 2047–2048. The wettest years are projected to occur in 2045–2046 for Spain and Tunisia, and in 2028–2029 for Lebanon. Although extreme drought events are not widely anticipated, localised severe dry periods emerge in many parts of the study areas. while in Lebanon, these conditions also extend into the winter and spring. These findings underscore the need for spatially targeted adaptation rather than uniform regional measures. Identifying both driest and wettest projected years enhances preparedness, informs water-resource optimisation, and supports agricultural land-use planning, especially in areas with favourable future climatic conditions. Integrating drought projections into multi-hazard planning (i.e., drought and floods) frameworks can further strengthen territorial resilience in regions facing increasing climate-related extremes. Full article

Understanding and predicting climate change impacts on the terrestrial water cycle is essential for water resources management and hazard prevention. This study aims to project future runoff of a densely-populated river basin, the Pearl River Basin (PRB), under different Shared Socioeconomic Pahway (SSP) scenarios, by combining the Soil and Water Assessment Tool (SWAT) model and the CMIP6 climate projections. Results show that climate change will significantly increase the runoff of the PRB, with changing rates of 0.21, 0.20, 0.11, and 0.17 mm/month/year for low- to high-emission scenarios SSP126, SSP245, SSP370, and SSP585, respectively. Future runoff exhibits strong seasonal and spatial variability due to complex changes in precipitation and potential evapotranspiration across the basin. The PRB may experience higher flood risks during the wet season under all SSP scenarios, driven by a ~15% increase in runoff during the wettest month during 2061–2100 relative to that of 2021–2060. Conversely, drought risks may escalate in the East River Sub-basin of the PRB during the dry season under the high-emission scenarios (SSP370 and SSP585), with a ~20% reduction in runoff during the driest month during 2061–2100 relative to that of 2021–2060. The highest-emission scenario (SSP585) may lead to the most drastic hydrological changes, including increased risks of flooding and drought across different parts of the PRB. Our findings suggest intensified water cycling and increased hydrological risks in the PRB under a changing climate, highlighting the necessity of future water resource management to consider potential climate change impacts to mitigate the risks of floods and droughts effectively. Full article

Based on precipitation extremes calculated from high-resolution daily observational data in East China during 1961–2014, the performance of 34 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are assessed in terms of climatology and interannual variability. Four extreme precipitation indices, including the total precipitation (Prcptot), the total precipitation for events exceeding the 95th percentile (R95p), and the maximum of 1-day (Rx1day) and 5-day (Rx5day) precipitation, are analyzed. Results show that the CMIP6 models demonstrate good performances in reproducing the climatological spatial distribution and interannual variability of precipitation extremes, with the best from Prcptot. Based on an integrated assessment of the above two factors, the models that perform relatively well for all four extreme precipitation indices are GFDL-CM4, MIROC6, EC-Earth3-Veg, EC-Earth3, and EC-Earth3-CC. Furthermore, the optimal multi-model ensemble (A-MME) constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet (dry) biases over the northern (southern) region of East China are all decreased. This may benefit from the improvement that A-MME can reproduce well the characteristics of moisture and vertical velocity. Full article

This study examines the hydrological response of the Klambu Dam Catchment in Central Java, Indonesia, to climatic and land cover changes from 2000–2023, with simulations extending to 2040. Utilizing CHIRPS satellite data calibrated with six ground stations, monthly precipitation and temperature datasets were analyzed and projected via linear regression aligned with IPCC scenarios, revealing a marginal temperature decline of 0.21 °C (from 28.25 °C in 2005 to 28.04 °C in 2023) and a 17% increase in rainfall variability. Land cover assessments from Landsat imagery highlighted drastic changes: a 73.8% reduction in forest area and a 467.8% increase in mixed farming areas, alongside moderate fluctuations in paddy fields and settlements. The Thornthwaite-Mather water balance method simulated monthly discharge, validated against observed data with Pearson correlations ranging from 0.5729 (2020) to 0.9439 (2015). Future projections using Cellular Automata-Markov modeling indicated stable volumetric flow but a temporal shift, including a 28.1% decrease in April rainfall from 2000 to 2040, contracting the wet season and extending dry spells. These shifts pose significant threats to agricultural and aquaculture activities, potentially exacerbating water scarcity and economic losses. The findings emphasize integrating dynamic land cover data, climate projections, and empirical runoff corrections for climate-resilient watershed management. Full article

Grouting to seal the recharge channels of water-bearing aquifers is an effective method for reducing mine water inflow. Evaluating effectiveness and establishing a hierarchical classification system are crucial for assessing project quality. Taking the grouting seal project of the Cambrian limestone aquifer recharge channels at Mine No.7 in the Pingdingshan Coalfield as a case study, this paper first comprehensively evaluates the grouting seal effectiveness based on the difference in dynamic water recharge to goaf before and after grouting, derived from long-term pumping test data. Further, six indicator factors—grout volume, grout volume per unit time, grout volume per unit thickness, final borehole pressure, penetration depth into Cambrian limestone, and variation in rock mechanical strength—were selected. Weights for these factors were determined by integrating the Analytic Hierarchy Process, entropy weight method, and composite weighting method. The TOPSIS model was applied to classify and rank the grouting seal effectiveness in six recharge channels. Results indicate that post-grouting water recharge from goaf decreased by 240.78 m³/h during dry season and 878.57 m³/h during wet season, confirming high-quality grouting seal. The grouting seal quality of the six recharge channels was ranked from highest to lowest as follows: NO.3 > NO.2 > NO.6 > NO.1 > NO.5 > NO.4. The evaluation results corresponded with the actual karst fissure development and distribution of goaf in the exposed recharge channels. Full article