Search Results (767)

Urban surface subsidence is primarily induced by intensive above-ground and underground construction activities and excessive groundwater extraction. Integrating InSAR techniques for safety monitoring of urban subway infrastructure is therefore of great significance for urban safety and sustainable development. However, single-track high-spatial-resolution SAR imagery is insufficient to achieve full coverage over large urban areas, and direct mosaicking of inter-track InSAR results may introduce systematic biases, thereby compromising the continuity and consistency of deformation fields at the regional scale. To address this issue, this study proposes an inter-track InSAR correction and mosaicking approach based on the mean vertical deformation difference within overlapping areas, aiming to mitigate the overall offset between deformation results derived from different tracks and to construct a spatially continuous urban surface deformation field. Based on the fused deformation results, subsidence characteristics along subway lines and in key urban infrastructures were further analyzed. The main urban area and the eastern and western new districts of Zhengzhou, a national central city in China, were selected as the study area. A total of 16 Radarsat-2 SAR scenes acquired from two tracks during 2022–2024, with a spatial resolution of 3 m, were processed using the SBAS-InSAR technique to retrieve surface deformation. The results indicate that the mean deformation rate difference in the overlapping areas between the two SAR tracks is approximately −5.54 mm/a. After applying the difference-constrained correction, the coefficient of determination (R²) between the mosaicked InSAR results and leveling observations increased to 0.739, while the MAE and RMSE decreased to 4.706 and 5.538 mm, respectively, demonstrating good stability in achieving inter-track consistency and continuous regional deformation representation. Analysis of the corrected InSAR results reveals that, during 2022–2024, areas exhibiting uplift and subsidence trends accounted for 37.6% and 62.4% of the study area, respectively, while the proportions of cumulative subsidence and uplift areas were 66.45% and 33.55%. In the main urban area, surface deformation rates are generally stable and predominantly within ±5 mm/a, whereas subsidence rates in the eastern new district are significantly higher than those in the main urban area and the western new district. Along subway lines, deformation rates are mainly within ±5 mm/a, with relatively larger deformation observed only in localized sections of the eastern segment of Line 1. Further analysis of typical zones along the subway corridors shows that densely built areas in the western part of the main urban area remain relatively stable, while building-concentrated areas in the eastern region exhibit a persistent relative subsidence trend. Overall, the results demonstrate that the proposed inter-track InSAR mosaicking method based on the mean deformation difference in overlapping areas can effectively support subsidence monitoring and spatial pattern identification along urban subway lines and key regions under relative calibration conditions, providing reliable remote sensing information for refined urban management and infrastructure risk assessment. Full article

Time-Domain Electromagnetic (TDEM) soundings are widely recognized as an effective method for subsurface characterization at intermediate depths. This study applies TDEM surveying to the municipality of Alfaro (La Rioja, Spain), where ten stations with 200 × 200 m loops were acquired and processed using Occam 1D inversion. The resulting models were integrated into a 3D environment in geomatic software (Seequent, Oasis montaj 2025.1) to generate a continuous geoelectrical volume of the subsurface. Three major resistivity domains were identified: a shallow resistive unit (40–80 ohm·m), an intermediate unit (20–40 ohm·m), and a deep conductive domain (<20 ohm·m). The pseudo-3D model revealed a thickening of the intermediate–resistive domain toward the central and western sectors, interpreted as the most favorable zone for groundwater extraction. This workflow demonstrates that integrating 1D TDEM inversion results into a pseudo-3D geoelectrical framework improves the spatial interpretation of resistivity distributions and provides a practical decision-support framework for identifying optimal drilling sites. Full article

This study develops a conjunctive-use framework that couples a surface water allocation model with the MODFLOW groundwater model to evaluate the interactions between surface water operations and groundwater recharge and pumping. The framework enables coordinated surface–groundwater management through iterative feedback between allocation decisions and groundwater responses. Three representative managed aquifer recharge cases in Taiwan are examined, each reflecting a distinct operational logic: (1) a space-for-time strategy that extends wet-season benefits through distributed recharge using irrigation surplus; (2) a centralized support–distributed feedback approach in subsidence-prone areas, where concentrated surface water is delivered to targeted zones while maintaining flexibility for upstream allocation; and (3) a time-for-volume mechanism that converts short-duration flood events into stable, long-term baseflow supply. The simulation results show that these strategies reduce downstream irrigation deficit ratios (e.g., from 0.58 to 0.22), raise groundwater levels by up to approximately 3.5 m in subsidence-sensitive zones, and substantially enhance drought resilience by reducing extreme reservoir depletion during prolonged dry periods. Overall, the proposed framework provides quantitative evidence and a practical planning tool for surface water-oriented conjunctive use, supporting more sustainable and resilient multi-source water management. Full article

High-precision and high-resolution surface deformation provide crucial constraints for studying the kinematic characteristics and dynamic mechanisms of crustal movement. Considering the limitations of existing geodetic observations, we used Sentinel-1 SAR images and accurate GNSS velocity to obtain a high-resolution three-dimensional (3D) surface velocity map across the Laohushan segment and the 1920 Haiyuan earthquake rupture zone of the Haiyuan Fault on the northeastern Tibetan Plateau. We tied the InSAR LOS (Line of Sight) velocity to the stable Eurasian reference frame adopted by GNSS. Using Kriging interpolation constrained by GNSS north–south components, we decomposed the ascending and descending InSAR velocities into east–west and vertical components to derive a high-resolution 3D deformation. We found that a sharp velocity gradient extending ~45 km along the strike of the Laohushan segment, with a differential movement of ~3 mm/a across the fault, manifests in the east–west velocity component, suggesting that shallow creep has propagated to the surface. However, the east–west velocity component did not exhibit an abrupt discontinuity in the rupture zone of the Haiyuan earthquake. Subsidence caused by anthropogenic and hydrological processes in the region, such as groundwater extraction, coal mining, and hydrologic effects, exhibited distinct distribution characteristics in the vertical velocity component. Our study provides valuable insights into the crustal movement in this region. Full article

Shale gas extraction is underway in the Karoo Basin. Previous oil and gas explorers abandoned several wells, and the abandonment statuses of these wells are unknown. Critically, improperly abandoned wells can provide a pathway for the leakage of stray gas into shallow aquifers and degrade water quality. To understand the abandonment integrity risk posed by these wells, a qualitative risk model was developed to assess the likelihood of well-barrier failure leading to a potential leak. The potential leak paths identified include zones with cement losses during grouting, casing corrosion, cement channels, failure to case and cement risk zones, uncased and uncemented sources, uncemented annuli, and unplugged wells. To confirm whether these wells are leaking, geochemical tracing of stray gas was integrated. Eleven of the fifty samples collected had dissolved hydrocarbon gas concentrations that were high enough to use isotopic analysis to determine the source. The results revealed microbial gas via fermentation and carbon dioxide reduction, thermogenic gas, and geothermal gas, as evidenced by larger δ¹³C₁ values and isotopic reversals associated with dolerite intrusions. The thermogenic-type gas detected in legacy abandoned wells and <1 km water boreholes adjacent to these wells serves as evidence that the downhole plugs did not maintain their integrity or were improperly plugged, whereas the thermogenic gas detected in >1 km water boreholes indicates leakage contamination due to natural fracture pathways. The presence of thermogenic gas in legacy wells and in groundwater boreholes <1 km from legacy wells implies that shale gas extraction using hydraulic fracturing cannot be supported in these situations. However, using safety buffer zones greater than 1 km from the legacy wells for shale gas drilling could be supported. Full article

Accurate forecasting of groundwater level dynamics poses a critical challenge for sustainable water management in arid regions. However, the strong spatiotemporal heterogeneity inherent in groundwater systems and their complex interactions between natural processes and human activities often limit the effectiveness of conventional prediction methods. To address this, a hybrid CNN-LSTM deep learning model is constructed. This model is designed to extract multivariate coupled features and capture temporal dependencies from multi-variable time series data, while simultaneously simulating the nonlinear and delayed responses of aquifers to groundwater abstraction. Specifically, the convolutional neural network (CNN) component extracts the multivariate coupled features of hydro-meteorological driving factors, and the long short-term memory (LSTM) network component models the temporal dependencies in groundwater level fluctuations. This integrated architecture comprehensively represents the combined effects of natural recharge–discharge processes and anthropogenic pumping on the groundwater system. Utilizing monitoring data from 2021 to 2024, the model was trained and tested using a rolling time-series validation strategy. Its performance was benchmarked against traditional models, including the autoregressive integrated moving average (ARIMA) model, recurrent neural network (RNN), and standalone LSTM. The results show that the CNN-LSTM model delivers superior performance across diverse hydrogeological conditions: at the upstream well AJC-7, which is dominated by natural recharge and discharge, the Nash–Sutcliffe efficiency (NSE) coefficient reached 0.922; at the downstream well AJC-21, which is subject to intensive pumping, the model maintained a robust NSE of 0.787, significantly outperforming the benchmark models. Further sensitivity analysis reveals an asymmetric response of the model’s predictions to uncertainties in pumping data, highlighting the role of key hydrogeological processes such as delayed drainage from the vadose zone. This study not only confirms the strong applicability of the hybrid deep learning model for groundwater level prediction in data-scarce arid regions but also provides a novel analytical pathway and mechanistic insight into the nonlinear behavior of aquifer systems under significant human influence. Full article

The ongoing global decline in groundwater levels poses significant challenges for sustainable water management. Satellite gravity missions, such as the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), provide valuable estimates of groundwater storage changes at regional scales. However, the relatively coarse spatial resolution of these satellite data limits their direct applicability to local groundwater management. In this study, we address this limitation for China by analyzing groundwater monitoring data from 108 cities with shallow groundwater use and 37 cities with deep groundwater use from the period 2019–2022, integrating in situ groundwater level records, official monitoring reports, monthly dynamic data, and GRACE-FO-derived groundwater storage estimates. Our findings reveal rapid groundwater depletion in northern China, especially in Xinjiang and Hebei Provinces. Fluctuations in shallow groundwater levels in Beijing and Jiangsu are closely related to precipitation variability. For deep aquifer regions, GRACE-FO-derived groundwater storage changes show a moderate Pearson correlation coefficient of 0.45 and groundwater level variations. Regional analysis for 2019–2021 in the Northeast Plain and the Huang–Huai–Hai Basin indicates better agreement between satellite-derived storage and groundwater levels, with a Pearson correlation coefficient of 0.58 in the Huang–Huai–Hai Basin. Groundwater level dynamics are strongly influenced by both precipitation and pumping, with an approximate three-month lag between precipitation events and groundwater storage responses. Overall, satellite gravity data are suitable for use in regional groundwater assessment and could serve as valuable indicators in areas with intensive deep groundwater exploitation. To enable fine-scale groundwater management, future work should focus on improving the spatial resolution through downscaling and other advanced techniques. Full article

Mine-induced surface subsidence threatens infrastructure and can trigger cascading geohazards, so accurate and computationally efficient monitoring and forecasting are essential for early warning. We integrate Persistent Scatterer InSAR (PS-InSAR) time series with a Bayesian-optimized CNN–LSTM designed for spatiotemporal prediction. The CNN extracts spatial deformation patterns, the LSTM models temporal dependence, and Bayesian optimization selects the architecture, training hyperparameters, and the most informative exogenous drivers. Groundwater level and backfilling intensity are encoded as multichannel inputs. Endpoint anchoring with affine calibration aligns the historical series and the forward projections. PS-InSAR indicates a maximum subsidence rate of 85.6 mm yr⁻¹, and the estimates are corroborated against nearby leveling benchmarks and FLAC^3D simulations. Cross-site comparisons show acceleration followed by deceleration after backfilling and groundwater recovery, which is consistent with geological engineering conditions. A symmetry-aware preprocessing step exploits axial regularities of the deformation field through mirroring augmentation and documents symmetry-breaking hotspots linked to geological heterogeneity. These choices improve generalization to shifted and oscillatory patterns in both the spatial CNN and the temporal LSTM branches. Short-term forecasts from the BO–CNN–LSTM indicate subsequent stabilization with localized rebound, highlighting its practical value for operational planning and risk mitigation. The framework combines automated hyperparameter search with physically consistent objectives, reduces manual tuning, enhances reproducibility and generalizability, and provides a transferable quantitative workflow for forecasting mine-induced deformation in complex goaf systems. Full article

Accurate prediction of shallow groundwater levels is crucial for water resource management in over-exploited regions like the North China Plain, where intensive pumping has created non-steady flow fields with strong spatial hydraulic interactions. Traditional approaches—whether physical models constrained by parameter equifinality or machine learning methods assuming spatial independence—fail to explicitly characterize aquifer hydraulic connectivity and effectively integrate multi-source monitoring data. This study proposes a Multi-source Fusion Spatiotemporal Graph Convolutional Network (MF-STGCN) that represents the monitoring well network as a hydraulic connectivity graph, employing graph convolutions to capture spatial water level propagation patterns while integrating temporal dynamics through LSTM modules. An adaptive fusion mechanism quantifies contributions of natural drivers (precipitation, evaporation) and anthropogenic extraction to water level responses. Validation using 518 monitoring stations (2018–2022) demonstrates that MF-STGCN reduces RMSE compared to traditional time series models, with improvement primarily attributed to explicit modeling of spatial hydraulic dependencies. Interpretability analysis identifies Hebi and Shijiazhuang as severe over-exploitation zones and reveals significant response lag effects in the Handan-Xingtai corridor. This study demonstrates that spatial propagation patterns, rather than single-point temporal features, are key to improving prediction accuracy in over-exploited aquifers, providing a new data-driven paradigm for regional groundwater dynamics assessment and targeted management strategies. Full article

Land subsidence caused by groundwater withdrawal remains a significant challenge in urbanized regions, requiring robust predictive models to manage its impact effectively. In this study, a set of coupled partial differential equations is formulated using Biot’s poroelasticity theory and Darcy’s law to model the hydro-mechanical behavior of a multi-aquifer system. The numerical models capture the coupled dynamics of fluid flow and subsurface deformation induced by groundwater table depression. Hydraulic head reductions, vertical compaction, and lateral deformation patterns over a 10-year pumping period are systematically examined. The results manifest that greater hydraulic gradients near geological discontinuities, such as bedrock steps, induce localized deformation and stress redistribution. While Terzaghi’s model effectively predicts vertical compaction in simple systems, Biot’s model accounts for lateral strain and coupled feedback mechanisms, providing a more comprehensive analyses and understanding of subsidence phenomena. This study highlights the importance of coupled hydro-mechanical modeling for accurately predicting land subsidence and offers insights into managing groundwater extraction in geologically complex regions. Full article

Sustaining irrigated agriculture under drought conditions with alternative water sources such as saline groundwater requires understanding their effects on salt-tolerant crops like pistachio. During recent California droughts, pistachio trees planted in 2002, 2009, and 2011 were irrigated with high-saline water containing traces of boron (B) and selenium (Se). In 2018, irrigation was divided so that half of the trees received low-saline water, while the others continued under high-saline irrigation. Three years later, nuts were harvested to evaluate how irrigation quality affected seed coats, the main storage site of phenolic antioxidants. Sixty seed coat extracts from both irrigation treatments were analyzed for antioxidant capacity (ABTS, DPPH, FRAP and Folin–Ciocalteu assays). Nuts from the oldest trees (planted in 2002) had the highest antioxidant capacity. High-performance liquid chromatography (HPLC) identified gallic acid and nine flavonoids. Catechin, procyanidin B1, cyanidin-3-O-galactoside, and eriodictyol were most abundant in the oldest trees. Irrigation salinity significantly affected gallic acid, quercetin, and isoquercetin, with higher concentrations detected in seed coats from trees receiving continued high-saline irrigation. These compound-specific shifts, together with strong age-dependent patterns, provide insight into how long-term salinity exposure influences phenolic composition in pistachio seed coats. Full article

Since 2006, Shanghai has implemented a comprehensive subsidence control system, which aimed at groundwater extraction restrictions, artificial recharge, and the control of engineering-based settlement. While significant results have been achieved, a systematic scientific evaluation of its specific effectiveness remains unclear. This study utilizes Sentinel-1 SAR data from 2015–2024 and employs SBAS-InSAR technology to obtain high-precision ground deformation fields across Shanghai. A Multilayer Perceptron (MLP) model was introduced to intelligently classify time-series deformation data, through which we identified five typical patterns: rapid subsidence, minor subsidence, fluctuating deformation, periodic deformation, and uplift. Building upon this foundation, the research integrates Shanghai’s subsidence control zoning data and four-phase land use data (1990, 2000, 2015, 2022) to systematically evaluate the regional effectiveness of subsidence control policies and reveal the driving mechanisms of different deformation patterns from a land use transition perspective. Results demonstrate that the stratified subsidence control policy has achieved significant results with distinct spatial differentiation characteristics: major prevention zones exhibit stable deformation (benign patterns reaching 72.03%), while general prevention zones display high-risk, highly dynamic characteristics (benign patterns accounting for only 29.73%). Further analysis reveals strong coupling between the five deformation patterns and land use history: rapid subsidence concentrates in historical reclamation areas, and uplift correlates with active intervention measures. These findings confirm that subsidence control effectiveness is closely associated with regional “land use background” and “development stage.” This study provides a scientific basis for optimizing precision governance strategies in Shanghai and offers a valuable reference framework and methodology for other coastal megacities worldwide facing similar challenges. Full article

In order to explore the co-evolutionary relationship between the functions of microbial communities and the chemical composition of groundwater in a hyporheic zone affected by groundwater exploitation along riverbank, we have taken the Huangjia water source area on the Liao River main stream in Shenyang as an example. DNA was extracted from microorganisms in the hyporheic zone affected by groundwater exploitation along the riverbank, and we conducted high-throughput sequencing to select the dominant bacterial strains from the indigenous bacteria. They are classified as the Proteobacteria phylum, the Actinobacteria phylum, the Firmicutes phylum, the Bacteroidetes phylum, the Chloroflexi phylum, and the Acidobacteria phylum. The dominant bacteria have a good correlation with Fe, Mn, and environmental factors (such as DO—dissolved oxygen, Eh—oxidation-reduction potential, etc.) in the hyporheic zone. The functions and activities of the superior bacterial strains exhibit a feature of co-evolution with the water’s chemical environment, which has certain response characteristics to redox zoning. Studying the co-evolution relationship between the microbial community structure and function in the hyporheic zone and the chemical composition of the groundwater can provide a microbiological theoretical basis for the redox zonation. It also offers reference for understanding the process of Fe and Mn migration and transformation in the hyporheic zone under the hydrodynamic conditions of groundwater exploitation along the riverbank. Full article

This study establishes an integrated “Detection–Decomposition–Interpretation” framework for geohazard assessment, with Tangshan City serving as a representative case. Using Sentinel-1 SAR images from 2020 to 2024, regional surface deformation was derived via the Small Baseline Subset InSAR (SBAS-InSAR) technique. Six categories of geohazards were systematically identified and classified: landslides, open-pit slope deformation, mining-induced subsidence, spoil heap deformation, tailings pond deformation, and reclamation settlement. A total of 115 potential hazards were spatially cataloged, revealing distinct zonation characteristics: the northern mountainous area is predominantly affected by landslides and open-pit mining hazards; the central plain exhibits concentrated mining subsidence; and the southern coastal zone is marked by large-scale reclamation settlement. For the southern reclamation area, where settlement mechanisms are complex, the Independent Component Analysis (ICA) method was applied to successfully decompose the deformation signals into three independent components: IC1, representing the dominant long-term irreversible settlement driven by fill consolidation, building loads, and groundwater extraction; IC2, reflecting seasonal deformation coupled with groundwater level fluctuations; and IC3, comprising residual noise. Time series analysis further reveals the coexistence of “decelerating” and “accelerating” settlement trends across different zones, indicative of their respective evolutionary stages—from decaying to actively progressing settlement. This study not only offers a scientific basis for geohazard prevention and control in Tangshan, but also provides a transferable framework for analyzing hazard mechanisms in other complex geographic settings. Full article

A manganese dioxide-modified carboxylated graphene oxide (MnO₂@CGO) nanocomposite was fabricated and utilized as a solid nanosorbent for extracting six organochlorine pesticides from environmental water samples. The target compounds, Hexachlorobenzene (HCB), β-Hexachlorocyclohexane (β-HCH), Heptachlor, Aldrin, Dieldrin, and o,p-Dichlorodiphenyltrichloroethane (o,p-DDT), were determined by micro-solid phase extraction (µ-SPE) coupled with gas chromatography–mass spectrometry (GC-MS) in selective ion monitoring mode. Key experimental factors influencing the extraction performance, such as sample pH, sorbent dosage, type and volume of eluting solvent, and time for desorption, were systematically optimized. Under the optimized conditions, the method showed good linearity (R² = 0.998–1.000) within the concentration range of 0.1–5 ng L⁻¹. The developed procedure was successfully applied to Nile River, agricultural wastewater, and groundwater samples, achieving recoveries between 87.1% and 101.2% with RSDs below 4.0%. The detection limits were 0.005–0.010 mg L⁻¹ at a signal-to-noise ratio of 3.0. Overall, the MnO₂@CGO-based µ-SPE method offers a sensitive, reliable, and straightforward approach for monitoring trace levels of organochlorine pesticides in environmental waters. Full article