Search Results (1,602)

Mining subsidence is a pervasive geohazard in coal basins, and precise and reliable deformation monitoring is essential to effective risk mitigation. Conventional time-series Interferometric Synthetic Aperture Radar (InSAR) suffers from vegetation-induced decorrelation and atmospheric delays. Most predictive models leverage only temporal information. We introduced an integrated DS InSAR + CNN LSTM framework for subsidence monitoring and forecasting. Forty-three Sentinel-1A scenes (2017–2018), corrected with Generic Atmospheric Correction Online Service for InSAR (GACOS) data, were processed to derive cumulative deformation, cross-validated against multi-view SBAS InSAR, and used to train a CNN LSTM network that predicts trends one year in advance. The findings indicate that (1) DS InSAR provides 2.83 times the monitoring density of SBAS InSAR, with deformation rate R² = 0.83, RMSE = 0.0028 m/a, and MAE = 0.0019 m/a at common pixels. The RMS average decrease in GACOS atmospheric delay phase correction is 2.52 mm. (2) High- and low-settlement zones comprise 0.11% and 92.32% of the area, respectively; maximum velocity reaches 190.61 mm/a, with a cumulative subsidence of −338.33 mm. (3) Across the five zones with the most severe subsidence, the CNN–LSTM model attains R² values of 0.97–0.99 and RMSE below 1 mm, markedly outperforming the standalone LSTM network. (4) Deformation correlated strongly with geological structures, groundwater decline (R² = 0.66–0.78), and precipitation (slope > 0.33), highlighting coupled natural and anthropogenic control. Full article

The exploitation of mineral resources often necessitates groundwater drainage, which may impact surrounding ecosystems, particularly vegetation. In this study, the effects of passive drainage in the Kornica-Popówka chalk mine in eastern Poland were analyzed using Sentinel-2 satellite images and the NDVI vegetation index. Groundwater monitoring wells were used to delineate the extent of the depression cone, representing areas of potentially altered hydrological conditions. NDVI values were analyzed across multiple time points between 2023 and 2024 to assess the condition of vegetation both inside and outside the depression cone. The results indicate no significant difference in NDVI values during the 2023–2024 study period for this specific chalk mine case between areas affected and unaffected by the depression cone, suggesting that vegetation in this region is not experiencing stress due to lowered groundwater levels. This outcome highlights the influence of other environmental factors, such as rainfall and land use, and suggests that the local geological structure allows plants to maintain sufficient access to water despite hydrological alterations. This study confirms the utility of integrating remote sensing with hydrogeological data in environmental monitoring and underlines the need for continued observation to assess long-term trends in vegetation response to mining-related groundwater changes. Full article

With the increasing demand for urban rail transit capacity, shield tunneling has become the predominant method for constructing underground metro systems in densely populated cities. However, the spatial interaction between shield tunnels and adjacent retaining structures poses significant engineering challenges, potentially leading to excessive ground settlement, structural deformation, and even stability failure. This study systematically investigates the deformation behavior and associated risks of retaining systems during adjacent shield tunnel construction. An orthogonal multi-factor analysis was conducted to evaluate the effects of grouting pressure, grout stiffness, and overlying soil properties on maximum surface settlement. Results show that soil cohesion and grouting pressure are the most influential parameters, jointly accounting for over 72% of the variance in settlement response. Based on the numerical findings, a Bayesian network model was developed to assess construction risk, integrating expert judgment and field monitoring data to quantify the conditional probability of deformation-induced failure. The model identifies key risk sources such as geological variability, groundwater instability, shield steering correction, segmental lining quality, and site construction management. Furthermore, the effectiveness and cost-efficiency of various grouting reinforcement strategies were evaluated. The results show that top grouting increases the reinforcement efficiency to 34.7%, offering the best performance in terms of both settlement control and economic benefit. Sidewall grouting yields an efficiency of approximately 30.2%, while invert grouting shows limited effectiveness, with an efficiency of only 11.6%, making it the least favorable option in terms of both technical and economic considerations. This research provides both practical guidance and theoretical insight for risk-informed shield tunneling design and management in complex urban environments. Full article

The extensive distribution of quaternary sediments and the extraction of underground resources in the Yellow River Delta (YRD) have resulted in significant land subsidence, which accelerates relative sea level (RSL) rise and heightens the risk of coastal inundation. This study uses Sentinel-1A (S1A) imagery and the time-series synthetic aperture radar interferometry (TS-InSAR) method to obtain subsidence information for the YRD. By integrating data from groundwater level monitoring wells, hydrogeological conditions, extensometer monitoring, and drilling wells, we analyze the causes of subsidence and the deformation response to the groundwater level changes in the corresponding aquifers. For the first time in the YRD, this study introduces the high accuracy CoastalDEM v2.1 digital elevation model, combined with absolute sea level (ASL) data, to construct a coastal inundation simulation. This simulation maps the land inundation caused by RSL rise along the YRD in different scenarios. The results indicate significant subsidence bowls in coastal and inland regions, primarily attributed to shallow brine and deep groundwater extraction, respectively. The main subsidence layers in inland towns have been identified, and residual deformation has been observed. Currently, land subsidence has caused a maximum elevation loss of 141 mm/yr in coastal YRD areas, significantly contributing to RSL rise. Seawater inundation simulations suggest that if subsidence continues unabated, 12.84% of the YRD region will be inundated by 2100, with 8.74% of the built-up areas expected to be inundated. Compared to global warming-induced ASL rise, ongoing subsidence is the primary driver of inundation in the YRD coastal areas. Full article

Groundwater depletion poses a critical challenge to global water security, threatening ecosystems, agriculture, and sustainable development. The Mississippi Delta, a region heavily reliant on groundwater for agriculture, has experienced significant groundwater level declines due to intensive irrigation. Traditional in situ monitoring methods, while valuable, lack the spatial coverage necessary to capture regional groundwater dynamics comprehensively. This study addresses these limitations by leveraging downscaled Gravity Recovery and Climate Experiment (GRACE) data to estimate groundwater levels using random forest modeling (RFM). We applied a machine-learning approach, utilizing the “Forest-based and Boosted Classification and Regression” tool in ArcGIS Pro, (ESRI, Redlands, CA) to predict groundwater levels for April and October over a 10-year period. The model was trained and validated with well-water level records from over 400 monitoring wells, incorporating input variables such as NDVI, temperature, precipitation, and NLDAS data. Cross-validation results demonstrate the model’s high accuracy, with R² values confirming its robustness and reliability. The outputs reveal significant groundwater depletion in the central Mississippi Delta, with the lowest water level observed in the eastern Sunflower and western Leflore Counties. Notably, April 2014 recorded a minimum water level of 18.6 m, while October 2018 showed the lowest post-irrigation water level at 54.9 m. By integrating satellite data with machine learning, this research provides a framework for addressing regional water management challenges and advancing sustainable practices in water-stressed agricultural regions. Full article

Carbon tetrachloride (CT) is a toxic volatile chlorinated hydrocarbon, posing a serious hazard to ecosystem and human health. This study discussed the bioremediation possibility of groundwater contaminated by CT. Enhanced reductive dechlorination bioremediation (ERD) was used to promote the reductive dechlorination process of CT by adding yeast extract as a supplementary electron donor. The microcosm samples of the Control and Experi group were setup in the experiment, and the CT degradation efficiency and microbial community structure changes over 150 days were monitored. The results showed that the Experi group achieved complete degradation of CT within 40 days, while the control group had no significant change. By analyzing the physical and chemical indexes such as VFAs, sulfate ions, oxidation–reduction potential, pH value and so on, the key changes in the degradation process of CT were revealed. Microbial community analysis showed that specific microorganisms such as Acinetobacter johnsonii, Aeromonas media and Enterobacter mori played a significant role in the degradation of CT. They may produce hydrogen through fermentation to provide electron donors for the reductive dechlorination of CT. In addition, the genes of reductive dehalogenase synthase related to CT degradation were also identified, which provided molecular evidence for understanding the biodegradation mechanism of CT. The results deliver a scientific basis for optimizing the bioremediation strategy of CT-contaminated groundwater. Full article

The evaluation of crop production that influences surface and groundwater quality is of growing importance in the context of agricultural sustainability in Europe. The primary aim of this study was to understand the relationship between gross nitrogen surplus in land and nitrate concentrations in surface and groundwater. The analysis was based on datasets collected from 2010 to 2021. Nitrate levels were categorized into three distinct quality classes based on the percentage of monitoring points, reflecting a spectrum from high quality, defined as nitrate levels below 25 mg/dm³, to poor quality, characterized by levels exceeding 50 mg/dm³. Redundancy analysis indicated that Gross Nitrogen Balance, a fertilizer use predictor, partially influences water quality, potentially due to long-term effects. Model selection for Gross Nitrogen Balance based on the AIC_c information criterion identified catch crops (or green cover), high-intensity agriculture, Natura 2000 sites, nitrogen-fixing plants, organic farming, fast-growing tree plantations, and EU27 states as predictors in the group of supported models. The best-fit model revealed differences between EU27 states for Gross Nitrogen Balance. Catch crops and Natura 2000 sites were also significant predictors, the former associated with a positive and the latter with a negative effect on nitrogen balance. In turn, WEI+ increased with nitrogen balance input but decreased with organic farming, indicating that promoting organic practices could help save water resources. Poland emerged as a country with relatively good water quality compared to several European counterparts, such as Denmark, Belgium, Malta, Czechia, Germany, and Lithuania. The implications of this research extend significantly to evaluation of the effects of the Common Agricultural Policy within the European Union. Full article

Elevated chloride (Cl⁻) concentrations in surface water and groundwater are an increasing concern in cold region urban environments, largely due to long-term road salt application. This study investigates the Cl⁻ distribution across southern Ontario, Canada, using geospatial methods to identify contamination hot spots and assess groundwater vulnerability at both regional and watershed scales. Chloride data from 2001 to 2010 and 2011 to 2020 were compiled from public sources and interpolated using inverse distance weighting. A regional-scale vulnerability index was developed using slope (SL), surficial geology (SG), and land use (LU) (SL-SG-LU), and compared it to a more detailed DRASTIC-LU index within the Credit River watershed. Results show that Cl⁻ hot spots are concentrated in urbanized areas, including the Greater Toronto Area and Golden Horseshoe, with some rural zones also exhibiting elevated concentrations. Vulnerability mapping corresponded well with the observed Cl⁻ patterns and highlighted areas at risk for groundwater discharge to surface waters. While the DRASTIC-LU method offered finer resolution, the simplified SL-SG-LU index effectively captured broad vulnerability trends and is suitable for data-limited regions. This work provides a transferable framework for identifying Cl⁻ risk areas and supports long-term monitoring and management strategies in cold climate watersheds. Full article

Groundwater is a strategically important source of drinking water supply in the arid and rural regions of Kazakhstan. The objective of this study is to assess the quality of groundwater at 11 water intakes located in the Kordai, Shu, and Merke Districts of the Shu transboundary basin in the Zhambyl Region. A comprehensive assessment of physicochemical parameters was performed, including concentrations of nitrates, sulfates, chlorides, iron, manganese, and other constituents, with subsequent comparison against regulatory limits defined by Order No. 26 of the Ministry of Health of the Republic of Kazakhstan (dated 20 February 2023), GOST standards, and ST RK ISO standards. The findings revealed that a number of water intakes exceeded the maximum allowable concentrations for specific indicators, especially in areas subject to significant anthropogenic pressure. The most vulnerable sources were identified near settlements characterized by intensive agricultural practices and inadequate wastewater treatment systems. Spatial comparison of the results enabled the identification of potentially contaminated areas as well as aquifer zones suitable for drinking water supply. The study emphasizes the importance of regular groundwater monitoring and spatial analysis techniques (GIS) to enhance the reliability and comprehensiveness of water quality assessments. The data obtained in this study can serve as a basis for informed decision-making in the area of water resource protection and contribute to the achievement of United Nations Sustainable Development Goal 6 (SDG 6)—to ensure availability and sustainable management of water and sanitation for all. Full article

Decades of unregulated zinc mining activities in the Mae Tao watershed, located in Mae Sot District, Tak Province, northern Thailand, have resulted in the pervasive contamination of agricultural soils with heavy metals, particularly cadmium (Cd), zinc (Zn), lead (Pb), and manganese (Mn). This legacy pollution has significantly impacted multiple environmental compartments—including surface water, groundwater, and sediments—and poses chronic health risks to local populations. This study investigates the key geochemical and physicochemical factors governing the leachability and mobility of these metals from contaminated soils and evaluates the associated human health risks. Controlled leaching experiments demonstrated that ionic strength exerts a more pronounced influence on metal mobilization than pH or other tested variables, suggesting that the electrolyte composition of pore water plays a dominant role in heavy metal transport. Despite elevated total concentrations of Cd, Zn, Pb, and Mn in the soils, hazard quotient (HQ) calculations indicated no significant non-carcinogenic risk under typical exposure scenarios. However, Cd exhibited a carcinogenic risk above the acceptable threshold at both average and peak soil concentrations, underscoring its potential to adversely affect human health. These findings enhance the understanding of heavy metal behavior in contaminated agroecosystems and provide a scientific basis for targeted risk management and long-term monitoring strategies in the Mae Sot region. Full article

Groundwater level (GWL) in unconfined aquifers is highly susceptible to climate variables and human activities, exhibiting nonlinear fluctuations; these can further contribute to or exacerbate environmental hazards, such as land subsidence. Understanding the relationship between GWL changes and external conditions is essential for effective groundwater resource management and ecological protection. However, this relationship remains unclear and variable. This study systematically analyzes the correlations between climate and human factors and GWLs, using data from monitoring stations in the unconsolidated sedimentary aquifers of Beijing, China. It evaluates the importance of influencing factors on GWL simulation accuracy and tests how different inputs affect simulation performance. The results indicate that human factors are more strongly correlated with GWLs, yet climate factors hold higher importance scores. In GWL simulations, different input variables yield varying accuracy, with the inclusion of precipitation notably decreasing simulation precision because of its lagged or indirect effects on groundwater levels. The variation in accuracy across monitoring stations further suggests that the primary differences may stem from the GWL data itself. These findings underscore the need for high-resolution, localized data and tailored input selection to improve GWL projections and inform adaptive water-resource strategies under changing climatic and anthropogenic pressures. Full article

A total of 162 groundwater samples were collected during November and December 2022 in the Xin’an River Basin during the dry season. In this research, the concentrations of various indicators in most samples did not exceed the prescribed standards. The indicators with the largest number of exceedances were iodine and manganese, with 22 and 23 samples, respectively. Overall, the groundwater quality in the Xin’an River Basin was generally good, with only 7 samples with the EWQI values greater than 150, which exhibited poor groundwater quality. The primary factors influencing groundwater quality were the concentrations of I, Mn, and Al, which were predominantly affected by water–rock interactions. Groundwater quality in the Xin’an River Basin was mainly influenced by natural factors rather than anthropogenic activities. Both the carcinogenic and non-carcinogenic health risks posed by groundwater in the Xin’an River Basin were higher for children than for adults. The long-term chronic cumulative effect was the most important factor contributing to both carcinogenic and non-carcinogenic health risks. Iodine presented the highest non-carcinogenic health risks for both adults and children. In regions where high-iodine groundwater was distributed, it is recommended to enhance the monitoring of iodine concentrations in the groundwater. Full article

With sub-millimeter deformation capture capability, InSAR technology has become an important tool for surface deformation monitoring. However, it is still limited by interferences like land subsidence and bridge deformation in long-term linear engineering monitoring, failing to accurately identify track deformation. Based on RadarSAT-2 and Sentinel-1A satellite data from 2013 to 2023, this study uses time-series InSAR technology (PS-InSAR) to accurately invert the track deformation information of the Beijing–Tianjin Intercity Railway (Beijing section) in the past decade. Key findings demonstrate (1) rigorous groundwater policies (extraction bans and artificial recharge) drove up to 48% regional subsidence mitigation in Chaoyang–Tongzhou, with synchronous track deformation exhibiting 0.6‰ spatial gradient; (2) critical differential subsidence identified at DK11–DK23, where maximum annual settlement decreased from 110 to 49.7 mm; (3) XGBoost-SHAP modeling revealed dynamic driver shifts: confined aquifer depletion dominated in 2015 (>60%), transitioned to delayed consolidation in 2018 (45%), and culminated in phreatic recovery–compressible layer coupling by 2022 (55%). External factors (tectonic/urban loads) played secondary roles. The rise in groundwater levels induces soil dilatancy, while the residual deformation in cohesive soils—exhibiting hysteresis relative to groundwater fluctuations—manifests as surface subsidence deceleration rather than rebound. This study provides a scientific basis for in-depth understanding of the differential subsidence mechanism along high-speed railways and disaster prevention and control. Full article

Groundwater, a critical source of drinking water, plays an essential role in global biogeochemical cycles, yet its microbial ecosystems remain insufficiently characterized, particularly in pristine karst aquifers. This study conducted high-resolution profiling of microbial communities and environmental parameters in two representative alpine karst aquifers in Slovenia: Idrijska Bela and Krajcarca. Monthly groundwater samples from the Krajcarca spring and Idrijska Bela borehole over a 14-month period were analyzed using whole-metagenome sequencing (WMS), UV-Vis spectroscopy, inductively coupled plasma mass spectrometry (ICP-MS), and isotopic analysis. The results revealed stable hydrochemical conditions with clear spatial differences driven by bedrock composition and groundwater residence time. Bacterial communities displayed strong correlations with hydrochemical parameters, while archaeal communities exhibited temporal stability. Functional gene profiles mirrored bacterial patterns, emphasizing the influence of environmental gradients on metabolic potential. No significant temporal changes were detected across two sampling campaigns (2016–2023), highlighting the resilience of these aquifers. This work establishes a valuable baseline for understanding pristine groundwater microbiomes and informs future monitoring and water quality management strategies. Full article

Groundwater quality in arid and semi-arid regions of Morocco is under increasing pressure due to both anthropogenic influences and climatic variability. This study investigates the physicochemical and heavy metal characteristics of groundwater across four Moroccan regions (Tangier-Tetouan-Al Hoceima, Oriental, Souss-Massa, and Marrakech-Safi) known for being argan tree habitats. Thirteen groundwater samples were analyzed for twenty-five parameters, including major ions, nutrients, and trace metals. Elevated levels of ammonium, turbidity, electrical conductivity, and dissolved oxygen were observed in multiple samples, surpassing Moroccan water quality standards and indicating significant quality deterioration. Inductively Coupled Plasma-Atomic Emission Spectroscopy (ICP-AES) detected arsenic concentrations exceeding permissible limits in sample AW11 alongside widespread lead contamination in most samples except AW5 and AW9. Spatial patterns of contamination were characterized using Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), K-means clustering, and GIS-based Inverse Distance Weighted (IDW) interpolation. These multivariate approaches revealed marked spatial heterogeneity and highlighted the dual influence of geogenic processes and anthropogenic activities on groundwater quality. To assess consumption suitability, a Water Quality Index (WQI) and Human Health Risk Assessment were applied. As a result, 31% of samples were rated “Fair” and 69% as “Good”, but with notable non-carcinogenic risks, particularly to children, attributable to nitrate, lead, and arsenic. The findings underscore the urgent need for systematic groundwater monitoring and management strategies to safeguard water resources in Morocco’s vulnerable dryland ecosystems, particularly in regions where groundwater sustains vital socio-ecological species such as argan forests. Full article