Environmental Earth Sciences最新文献

In the era of climate change, sustainable groundwater management has become increasingly critical, as climate-driven changes in precipitation patterns affect groundwater recharge and availability, emphasizing the need for effective regulation. The Total Groundwater Quantity Management (TGQM) framework aims to ensure sustainable groundwater extraction by comparing actual usage with development potential within designated groundwater management units (GMUs). GMUs are defined based on hydrogeological characteristics, groundwater–surface water interactions, and geographic boundaries. A regression tree model was used to estimate groundwater recharge rates, utilizing water level data from 3,886 observation wells and groundwater usage data from 7,693 wells. Based on this, a framework was developed to assess over-extraction by evaluating the ratio of groundwater usage to development potential for each GMU. When applied to 609 GMUs in Chungcheongnam-do, South Korea, the TGQM framework found that 18.4% of GMUs exceeded 60% of their development potential, with 4.3% surpassing 100%. Analysis of groundwater usage relative to level changes showed that groundwater levels declined when usage exceeded 60%, and all GMUs exhibited declining trends when usage surpassed 80%. Management thresholds were set at 60%, 80%, and 100%, marking caution, warning, and critical stages, respectively. This system of groundwater management, based on the usage-to-development potential ratio, can guide governmental interventions and promote scientifically informed groundwater policies for sustainable resource use.

Sediment yield prediction is vital for sustainable watershed management, particularly in data-scarce regions. This study, conducted in the Göksun Çayı Karaahmet sub-basin, Türkiye, evaluated whether sediment connectivity indices can reproduce outputs from the Revised Universal Soil Loss Equation (RUSLE) and Modified Universal Soil Loss Equation (MUSLE). Sediment yield was modeled for 196 sub-catchments and 69 rainfall events over 10 years using GIS-based factors: rainfall erosivity, soil erodibility, slope length-steepness, land cover, and hydrological parameters. Despite different assumptions (rainfall erosivity versus runoff and peak discharge), RUSLE and MUSLE showed strong agreement (R² = 0.87 at the event scale; R² = 0.93 at the sub-catchment scale). Predicted sediment yields ranged from 0.02 to 16.46 t ha^-1 (MUSLE) and 0.04–10.63 t ha^-1 (RUSLE/SDR), with mean values of 0.89 and 0.96 t ha^-1, respectively. Sediment connectivity indices-including the Index of Connectivity (IC), Sediment Delivery Ratio (SDR), and Topographic Wetness Index (TWI), were applied as inputs to five machine learning (ML) models (XGBoost, Random Forest, k-NN, SVR, and ANN). XGBoost and Random Forest achieved the best performance (R² = 0.912–0.942, RMSE = 0.065–0.089, MAE = 0.047–0.055), reproducing empirical outputs. IC, SDR, and TWI were dominant predictors. These results demonstrate that connectivity metrics integrated with ML can emulate empirical erosion models, offering a scalable, data-efficient alternative for ungauged basins. However, because the models were trained on RUSLE/MUSLE outputs from 69 events under static land use and climate, they may underpredict extreme sediment events and require field validation before operational use.

Access to clean water is a fundamental human right, yet over two billion people face water scarcity–a crisis intensified by population growth and climate change. This study presents a data-driven analysis of atmospheric water yields at 30 globally distributed locations under varying climate stress. Using hourly ERA5 data from 2000 to 2022, we quantified the monthly average daily water extraction potential of solar-powered atmospheric water harvesting (AWH) systems. Statistically significant changes in AWH performance ((p < 0.05)) were found at 25 locations, affecting 61 of 360 location-month combinations (17%), with trends ranging from –65% to +55% relative to the 23-year average. Seasonal fluctuations were only slightly surpassed by long-term trends in three cases. No strong correlation with climate zones was found, but seasonal effects were evident, with a predominance of negative trends around mid-year and positive trends around the turn of the year. Correlation and sensitivity analyses identified relative humidity as the primary driver of AWH efficiency, while solar radiation and air temperature played secondary roles. AWH systems yielded between 650 and 13,070 ml m(^{-2}) day(^{-1}) across sites. These findings highlight AWH as a robust, scalable, and climate-resilient solution to support SDG 6 in water-stressed regions.

Groundwater provides the principal irrigation lifeline for the semi-arid reaches of the Malwa Region of Northwestern India, yet its long-term sustainability remains increasingly uncertain. Using 25 years (2000–2024) of Central Ground Water Board (CGWB) monitoring-well data, this study mapped annual pre- and post-monsoon groundwater levels and identified statistically significant declines in 12 of 14 districts. It is observed that zones with water tables deeper than 20 m expanded dramatically from 2 km^² in 2000 to 16,559 km² in 2024, where the steepest depletion observed in Sangrur and Barnala district with − 1.35 m yr^⁻¹ and − 1.26 m yr^⁻¹ depletion respectively, marking the region’s principal hotspot of depletion. A concurrent doubling of registered irrigation tubewells from 0.56 million to 1.12 million, aligns with flat-rate electricity subsidies and intensification of the rice–wheat rotation, highlighting policy-driven over-abstraction. Additionally, Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data reveal a persistent west-to-east rainfall gradient (115–1365 mm yr^⁻¹), offering limited natural recharge where depletion is most severe. The integrated attribution analysis further revealed that tubewell density (r = 0.67) and paddy acreage (r = 0.58) exert the strongest controls on groundwater decline, jointly explaining 71% of the variation in depletion trends in the multiple regression model. Random Forest regression also confirmed tubewell density as the dominant predictor of long-term groundwater decline. Overall, the results reveal an intensifying human influence over groundwater decline, driven primarily by the expansion of irrigation tubewells and the persistence of the rice – wheat system. These findings call for integrated policy action that combines demand management, crop diversification, and managed aquifer recharge with rationalized energy pricing to moderate groundwater abstraction. The study offers a concise, data-driven framework that can guide adaptive groundwater governance and sustainable water-energy planning across semi-arid agricultural regions.

Liquid nitrogen (LN₂) fracturing represents an innovative waterless permeability enhancement technology, capable of effectively improving coal seam permeability. To quantify pore space distribution heterogeneity and permeability anisotropy, the pore microstructure of low-order bituminous coal after LN₂ fracturing was characterized via Micro-CT scanning. Based on the three-dimensional reconstructed gas pore model, COMSOL software was used to simulate the single-phase seepage process. The results show that the frequency distribution histograms of pore throat parameters follow a lognormal distribution. LN₂ fracturing results in an increase in the number of pore throats and an expansion of their radius range. Specifically, the average coordination number increases by 0.86, while the average tortuosity decreases by 0.75. For fractured coal samples, the Z-direction manifests the highest porosity and connectivity, with porosity increasing by 182%. The pore surface area and shape factor follow a logarithmic distribution, while the pore volume, equivalent diameter, and sphericity display a power function distribution. A positive correlation exists between pore radius and coordination number, whereas a negative correlation is observed between throat radius and pore-throat ratio. The gas flowed along the X, Y, and Z directions, respectively, with the pore pressure gradually decreasing along the flow direction. Notably, the pressure exhibited the most rapid changes in narrow and rough regions. Additionally, permeability and seepage velocity exhibited pronounced directional anisotropy, while LN₂ fracturing enhanced seepage velocities across all directions. With increasing pressure gradient, seepage velocity displayed a nonlinear upward trend in each direction.

Accurate monitoring of drought conditions requires the use of quantitative indices that capture the variability of precipitation and other climatic parameters. The development and comparison of such indices provide valuable insights for both scientific understanding and practical applications in drought management. This study investigated historical drought trends in Türkiye's Seyhan, Ceyhan, and Asi River basins by employing indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Discrepancy Precipitation Index (DPI), and New Drought Index (NDI). Given the growing importance of understanding drought dynamics, these indices were selected to ensure a comprehensive evaluation by incorporating distinct climatic parameters such as precipitation, evapotranspiration, and temperature. 13 meteorological stations were examined to ensure data reliability and accuracy for the years 1970 to 2021. The drought indices were calculated, and their temporal trends were analyzed using the Innovative Trend Analysis (ITA) method. The 52-year dataset was divided into three distinct periods for detailed trend evaluation. Partitioning the 52-year record for ITA revealed widespread negative NDI trends in the third period (nearly all stations) with a persistent wetting signal at Karataş, while RDI declines were pronounced at Karaisalı and Kahramanmaraş. Correlation analyses revealed that SPI and RDI showed strong alignment due to their common reliance on precipitation data. In contrast, NDI, which includes temperature as a parameter, exhibited broader sensitivity, indicating its ability to detect extreme wet and drought periods more effectively. Findings highlighted significant spatial and temporal variability in drought conditions. Across 13 stations (1970–2021), all four indices converged on the same extreme years, six wet (1976, 1981, 1987, 1988, 1997, 2009) and six dry (1989, 1990, 1993, 2013, 2017, 2020), demonstrating cross-index consistency in event detection. Overall, the study underscores the critical need for employing multiple drought indices to capture complex climatic dynamics accurately. It also emphasizes the utility of integrating newly developed indices like DPI and NDI into drought monitoring frameworks. The findings suggest that future drought management strategies should consider index-specific sensitivities and regional climatic characteristics for precise drought assessments.

Production practices in the mining industry during the last century have left numerous inactive facilities that current administrations have to deal with. In the case of tailings storage, the risk of pollution dispersion or large-scale damage caused by stability failures requires specific actions. In southern Spain, 28 abandoned tailings dams in the mining districts of Mazarrón, Cartagena and La Unión and 59 in the mining districts located in Andalucian Provinces, have been classified as hazardous for potential pollution risk, according to European regulations. In this document, we gather the experiences of 23 case studies in tailing decommission projects planned during the 2010-24 period, focusing on the most recent case of the San Cristobal-II tailings dam (SC-II). The actions conducted consist essentially of sealing, introduction of drainage elements, slope reprofiling and surface revegetation. The geotechnical characterization and monitoring conducted during decommissioning have emphasized that action must focus on pore water pressure control throughout all the phases of the project. The analysis of the actions involved in the decommissioning projects shows some positive experiences but also the need to improve in-depth geotechnical data acquisition, to ensure long-term safety while optimizing the decommissioning costs.

To investigate the shale damage mechanism caused by long-term contact between water-based drilling fluid and the borehole wall, we systematically studied the dynamic evolution of shale pore structures at different hydration times through fixed-point observation experiments. Results show that after 48 h of shale hydration, the maximum pore diameter increases from 6.52 to 9.66 nm, while the number of pores increases from 136 to 432. Hydration primarily promotes mineral dissolution on the shale surface, exerting a strong influence on pore number and a comparatively smaller effect on pore diameter. The porosity of the core before hydration is 2.1%–5.5% and increases to 2.4%–13.7% after hydration. The porosity increases to varying degrees, and the increase multiple is between 0.14 and 1.50. The effect of hydration is more pronounced in rocks with higher initial porosity. Shale hydration also exhibits clear fractal characteristics, with the fractal dimension increasing from 2.663 to 2.8735 within 48 h. The fractal characteristics of pores before and after hydration and the hydration time conform to the logarithmic function relationship. This study elucidates the evolutionary patterns of fractal characteristics in shale pores and develops a model to describe the relationship between fractal dimension and hydration time. The model provides a scientific foundation for investigating the dynamic evolution of pore structures and the causes of wellbore instability during shale hydration.

Heavy metal(loids) (HMs), which can be carcinogenic, cytotoxic, and mutagenic, can pose a threat to fauna, flora, and humans. In the mining industry, large amounts of HMs released uncontrolled as a result of activities such as extraction, grinding, clustering of mineral ores, and dumping of wastes in open areas. Perlite is a naturally occurring glassy volcanic alumina silicate rock that is mined and used all over the world. Perlite is utilized in the construction, agriculture, food, pharmaceutical, and chemical industries. This study focuses, for the first time, on the determination of HM contents of perlites produced as a result of mining in Türkiye and the assessment of potential health risks (PHRs) arising from HMs for quarry workers. The concentrations of HMs in 126 perlites samples collected from 12 quarries located in different geographical regions of Türkiye were analyzed by an energy-dispersive X-ray fluorescence (EDXRF) spectroscopy. The hazard index (HI) and total carcinogenic risk (TCR) index were estimated to assess non-carcinogenic and carcinogenic PHR for workers via three exposure pathways. The average concentrations of HMs analyzed in perlites samples were 4.2 (As), 4.3 (Cu), 7.0 (Co), 7.1 (V), 19.8 (Ni), 26.4 (Pb), 31.1 (Zn), 64.9 (Cr), 93.7 (Zr), 383.5 (Mn), 528.3 (Ti) and 6585.4 (Fe) mg kg⁻¹ dw, which were below the upper continental crust average, exception for Pb. All HI and TCR values revealed that the non-carcinogenic and carcinogenic PHRs for adult quarry workers exposed to all HMs in the studied perlites were in the acceptable range.

Oil pollution can modify the compression characteristics of soil, impacting its bearing capacity and stability. In addition, oil pollutants can spread to the surrounding environment through soil pores and groundwater systems, causing extensive environmental pollution. Simultaneously, it elevates the likelihood of fire and other accidents, posing a risk to the safe production of oil. This article aims to explore the compression characteristics and resistivity response of oil contaminated soil. It conducts uniaxial compression tests on oil contaminated soil under varying oil contents (0%, 3%, 6%, 9%, 12%, 15%) and moisture contents (5%, 10%, 15%), monitors the changes in resistivity simultaneously. The results indicate that the compressive strength of the soil decreases with increasing moisture content in oil contaminated soils. The compressive strength exhibits a trend of initially increasing and then decreasing with higher oil content, reaching its peak value when the oil content is 3%. During uniaxial compression, the soil resistivity generally decreases at first and then stabilizes as strain increases. Before the uniaxial compression test, soil resistivity decreases with increasing moisture content, but the variation differs under different oil content conditions. When the moisture content is 5%, the resistivity generally increases with rising oil content. However, when the moisture content reaches 15%, the dominant conductive mechanism shifts from oil-controlled to water-controlled, leading to a decrease in resistivity with increasing oil content. After the uniaxial compression test, soil resistivity is primarily influenced by moisture content. The resistivity gradually decreases as moisture content increases and shows little sensitivity to oil content. By monitoring changes in soil electrical resistivity, the impact of oil pollution on the foundation of structures and the surrounding environment can be predicted in a timely manner, providing a basis for preventive maintenance.