Search Results (1,979)

Land subsidence in coastal reclamation areas has emerged as one of the critical hidden hazards for coastal cities. This paper presents an integrated InSAR and coastline-change framework for land subsidence monitoring and driving-factor analysis in coastal reclamation cities. Taking the Fangchenggang City, China, as the study area, we utilized 266 scenes of Sentinel-1A SAR images (2016–2025) from the European Space Agency (ESA) and applied time-series SBAS-InSAR to obtain a 10-year time-series monitoring result of land subsidence, with cross-validation against PS-InSAR showing an RMSE below 4 mm at four checkpoints. Furthermore, influencing factors were analyzed by integrating data on coastline changes, precipitation, and groundwater indicators. The conclusions of this paper are as follows: (1) Seven distinct land subsidence funnels in Fangchenggang City from 2016 to 2025 were identified for the first time. Spatially, land subsidence exhibits significant heterogeneity, primarily concentrated in the coastal reclamation areas of the Qisha Peninsula and the Yuwan Peninsula, the maximum subsidence rate reached as high as −163.53 ± 4.90 mm/yr. Temporally, the subsidence rate in the study area shows a gradual deceleration trend over time. (2) The coastline change results from 1964 to 2025 reveal a three-stage temporal characteristic: the land area increased by 2.23 ± 4.51 km², 14.28 ± 6.19 km², and 23.31 ± 4.51 km² during the periods of 1964–1995, 1995–2008, and 2008–2025, respectively. The time-series InSAR results and coastline change results demonstrate that coastal reclamation is the primary factor contributing to land subsidence in this study area. (3) Apart from land reclamation, driving factors such as precipitation and groundwater indicators also show a slight correlation with land subsidence. Full article

Earthquake-induced fracturing and microcrack development in subsurface strata are widely recognized as important processes influencing seepage and the hydrological behaviour of surface water bodies, particularly in tectonically active mountainous terrains. However, the hydrogeological response to repeated low-magnitude (<4) seismic events remains poorly understood. This study presents an integrated geoelectrical and remote sensing investigation of the Nagi Lake region in the Sikkim Himalaya, India, based on Vertical Electrical Sounding (VES) surveys conducted in May 2022 and March 2026, following a seismic sequence of 74 low-magnitude earthquakes recorded during February 2026. Comparative analysis of four VES profiles (VES1–VES4), supported by validatory factor analysis, reveals spatially heterogeneous changes in subsurface electrical characteristics between the two survey periods. VES1, VES2, and VES3 indicate reduced signatures of pre-existing microcracks that are consistent with sediment densification and partial sealing, whereas VES4 suggests localized development or persistence of microfractures. Because the surveys span approximately four years, these changes likely reflect the combined influence of long-term hydrogeological, environmental, and geomorphic processes, with the February 2026 seismic sequence representing one potential contributing factor rather than the sole driver. To further evaluate ground deformation, Sentinel-1A Synthetic Aperture Radar (SAR) data acquired between January 2019 and March 2026 were analysed using Persistent Scatterer Interferometric SAR (PS-InSAR). The results indicate cumulative Line-of-Sight (LOS) displacements ranging from −17.9 cm (movement away from the satellite) to +3.5 cm (movement toward the satellite) in the vicinity of Nagi Lake, reflecting localized surface deformation with millimetre-scale precision. These observations provide complementary evidence of ongoing subsurface adjustment that may promote sediment compaction and microcrack modification. Overall, the study demonstrates measurable temporal changes in the subsurface structure of the Nagi Lake area and suggests that repeated low-magnitude seismicity may contribute to subsurface restructuring alongside other environmental processes. The findings highlight the value of integrating geophysical monitoring and satellite-based deformation analysis for understanding groundwater–surface water interactions and supporting the sustainable management of vulnerable Himalayan water bodies. Full article

Rapid urbanization and inadequate sanitation infrastructure threaten water security in many sub-Saharan African cities. This study aimed to provide an integrated assessment of groundwater, surface water, and wastewater quality in Bangui by characterizing physicochemical parameters, trace metals, and microbiological indicators, and by identifying potential contamination sources and pathways among these water compartments. A total of 28 water samples were collected from groundwater, surface water, and wastewater sites. Physicochemical parameters, major ions, trace metals, and microbiological indicators were analyzed using standardized methods, including ion chromatography, ICP-OES, ICP-MS, and membrane filtration. Results revealed a clear contamination gradient. Wastewater showed the highest electrical conductivity, turbidity, chloride concentrations, and microbial loads, reaching 2.41 × 10⁶ CFU/100 mL for total coliforms and 1.93 × 10⁶ CFU/100 mL for fecal coliforms. Groundwater exhibited high nitrite levels and low dissolved oxygen, indicating vulnerability to sewage infiltration. Surface waters were characterized by high turbidity and widespread fecal contamination despite relatively good oxygenation. In contrast, trace metal concentrations generally remained below World Health Organization guideline values. Geochemical analyses identified distinct elemental signatures for each water type. Microbiological contamination emerged as the dominant water quality concern. High fecal coliform/fecal streptococci ratios (13.08-22.16) indicated predominantly human-derived pollution linked to untreated wastewater and inadequate sanitation systems. The association between elevated nitrite concentrations and fecal indicators suggests active contamination pathways connecting wastewater, surface water, and shallow aquifers. These findings highlight the urgent need for improved wastewater management, groundwater protection, and long-term monitoring to ensure sustainable urban water security in Bangui. Full article

Water security is a significant challenge for the Saudi Arabia Kingdom’s development and stability, affecting other economic sectors beyond the water sector. Insufficient water resources are causing economic and social crises; addressing this issue is crucial for the country’s growth and stability. This study aims to manage water resources in central Saudi Arabia (Wadi AS SAHBAA) through a two-level approach. The first level involves extracting rainfall amounts from satellite imagery to predict future rainfall intensity using PERSIANN-CCS-CDR data. The second level focuses on monitoring groundwater recharge using geographic information systems (GIS) and remote sensing techniques. The study further seeks to understand rainstorm behavior influenced by climate variability and applies geomatics techniques for quantitative analysis. The results show that the Wadi AS SAHBAA basin receives an annual precipitation of 116.6 mm/year and mean annual precipitation of 9.7 mm. The year 2019 experienced the highest recorded precipitation, reaching 222.3 mm and mean annual precipitation of 18.5 mm. Between 2013 and 2019, the AS SAHBAA region experienced increased rainfall driven by intense storm events; however, it declined during the period 2020–2022. Moreover, 2021 recorded the lowest annual precipitation of 53.8 mm with mean annual precipitation of (4.5 mm), possibly linked to reduced storm activity due to the COVID-19 pandemic. The study uses several methods to estimate groundwater recharge from rainfall and concludes that the average infiltration during 2013–2022 was varying from 1.59–36.63 mm, representing about between 1.03 and 28.5% of total rainfall. This is reflected in groundwater storage capacity, which ranges from approximately 1.65 to 38.27 million m³ yearly. This study provides a framework for monitoring precipitation and groundwater recharge and offers practical recommendations for regional development and sustainable water management. Full article

Yellow River irrigation districts must maintain food production under variable inflows, rigid diversion quotas, sedimentation, groundwater depletion, and soil salinization. This systematic review synthesized 79 journal articles from Web of Science and CNKI to clarify how resilience can be assessed and managed at the irrigation-district scale. The evidence indicates that resilience is a time-dependent combination of resistance, recovery, adaptability, and transformability within a coupled water source–canal–field–drainage–ecology–institution system. Although composite indices and hydrological–crop models have advanced, three gaps remain: operational thresholds rarely connect indicators to failure and recovery; farmer and institutional feedbacks are weakly represented; and assessments seldom translate into executable schedules. We, therefore, propose an irrigation-district-specific framework that couples water, sediment, salt, crops, ecology, and governance across basin–district–field scales without transferring risk between scales. Management priorities differ spatially: upstream districts require coordinated water–salt control; middle-reach well–canal systems require surface-water substitution and groundwater recovery; and downstream diversion districts require multi-source allocation and adaptive intake. A digital twin-based closed loop—continuous monitoring, forecasting, optimization, operational commands, and feedback correction—can translate diagnosis into canal rotation, recharge, drainage, and emergency actions. This review provides operational indicators and a decision-oriented research agenda for resilient irrigation modernization. Full article

The Middle Route of the South-to-North Water Diversion Project (SNWD-MR) serves as a strategic infrastructure critical to safeguarding water security in Northern China. Traversing complex geographical units, the project is perpetually exposed to long-term risks of land subsidence. Conventional Interferometric Synthetic Aperture Radar (InSAR) monitoring is hampered by waterbody isolation, causing spatial discontinuities in the retrieved deformation fields; furthermore, relying solely on deformation metrics fails to comprehensively quantify multidimensional risks. To address these issues, this study proposes an integrated assessment framework that couples time-series InSAR observations with the Analytic Hierarchy Process-Fuzzy Comprehensive Evaluation (AHP-FCE) model. To specifically mitigate the challenge of waterbody isolation, we developed a connectivity-aware multiscale down-sampling phase unwrapping strategy. By exploiting cross-canal bridges to construct a spatial connection network, a highly accurate, spatiotemporally continuous deformation field across the entire alignment was successfully reconstructed. Using the derived deformation field as the core dynamic indicator, an AHP-FCE model integrating hydrogeological features and human perturbations was constructed. A complementary evaluation process comprising sensitivity analysis and an internal physical consistency assessment was subsequently implemented. The results demonstrate that (1) the proposed algorithm effectively resolves the spatial discontinuity issue of the cross-canal deformation fields, reducing the deformation-velocity RMSE from 7.9 to 5.7 mm/y, corresponding to an approximately 27.8% reduction in RMSE relative to the traditional Minimum Cost Flow (MCF) method; (2) land subsidence along the alignment exhibits prominent spatial heterogeneity, with the northern Henan and southern Hebei sections identified as very-high-risk zones; and (3) InSAR deformation magnitude and the groundwater elevation indicator emerge as the most influential factors in the modeled risk distribution. Overall, this study expands conventional deformation monitoring into a systematic, quantitative risk assessment framework, thereby providing scientific insights and theoretical support for the early warning of geo-hazards and the smart operation and maintenance of large-scale water diversion projects. Full article

Land subsidence induced by excessive groundwater withdrawal has become one of the most significant geohazards affecting the Konya Closed Basin, Turkey. Although previous studies have successfully monitored ground deformation using geodetic and remote sensing techniques, limited attention has been devoted to transforming deformation measurements into quantitative, spatially classified hazard information. This study presents a severity-based framework for delineating land-subsidence hazard zones and critical hotspots in the Konya metropolitan area by integrating SBAS-InSAR observations and spatial statistical analyses. A total of 82 Sentinel-1 SAR acquisitions (41 ascending and 41 descending images) acquired between January 2023 and May 2026 were processed using the Small Baseline Subset (SBAS) technique. Ascending and descending line-of-sight deformation measurements were combined to derive vertical deformation rates, which were integrated with spatial statistical indicators and a composite severity index to quantify deformation clustering and classify subsidence severity. Hazard zones and critical hotspot areas were delineated through severity-based classification and spatial connectivity analyses. The results reveal a continuous north–south-oriented subsidence deformation belt extending across the eastern Konya. Maximum vertical subsidence rates exceeded 230 mm/yr, while spatial statistical analyses confirmed strongly clustered and statistically significant deformation patterns. Severity-based hazard zonation identified four hazard classes and a continuous high-hazard corridor. Clustering analysis further identified a dominant hotspot belt covering approximately 160 km², with mean subsidence rates of approximately 142 mm/yr. A sensitivity analysis of the composite severity index weighting scheme, the spatial statistical neighborhood distance, the DBSCAN clustering parameters, and the number of Jenks severity classes confirmed that the resulting hazard zones and critical hotspot belt are robust to reasonable parameter variations. The findings demonstrate that land subsidence in Konya is organized as a spatially continuous regional-scale deformation system rather than a collection of isolated subsidence centers. The proposed framework transforms InSAR-derived deformation measurements into quantitative, decision-support hazard information and provides a transferable methodology for land-subsidence hazard assessment in groundwater-stressed urban environments. Full article

Landslides in weathered gypsum deposits present significant geotechnical challenges because progressive weathering, groundwater fluctuations, and residual strength degradation strongly influence slope stability. This study investigates the failure mechanism and remediation of a large translational landslide in weathered gypsum deposits in Çankırı, Türkiye. An integrated engineering geological assessment was conducted using data from 16 boreholes, laboratory tests, and groundwater/inclinometer monitoring records, followed by residual shear strength back-analysis and slope stability evaluation. A three-dimensional geological model was developed, and cross-sections were analyzed using the Morgenstern–Price limit-equilibrium method. Back-analysis identified residual shear strength parameters of c′ = 7.5 kPa and ϕ′ = 10° for the weathered gypsum, while laboratory direct shear tests yielded c′ = 4.0 kPa and ϕ′ = 9.9°. The friction angles obtained from the two approaches are nearly identical, whereas the back-calculated cohesion is slightly higher than the laboratory-derived value. Back-analysis parameters were used to design remediation measures, including slope unloading, rock buttress construction, toe fill improvement, and surface/subsurface drainage. Stability analyses increased the factor of safety to 1.76 under static loading, while pseudo-static analyses satisfied the recommended seismic design criterion (FS ≥ 1.10). Equivalent-linear Newmark analyses predicted a permanent displacement of 15 cm, within acceptable limits. The methodology provides a practical framework for assessing and stabilizing landslides developed in weathered gypsum deposits in seismically active regions. Full article

To support groundwater protection and sustainable utilization in southern Sichuan, this study aims to clarify the multi-year variation characteristics of groundwater levels (GWLs) and identify their main driving factors in the Yibin region. In this paper, 2019–2024 GWL monitoring records, hydrometeorological data, and multi-source geospatial datasets were integrated. Trend analysis, centroid migration modeling, continuous wavelet transform, Geodetector, and Fast Fourier Transform-based cross-correlation analysis were used to examine GWL dynamics and their controlling factors. The results show that GWL depth exhibits a distinct “shallow-northwest to deep-southeast” pattern, which is closely associated with regional aquifer lithology and hydrogeological conditions, with the most pronounced fluctuations occurring in the northwest. From 2019 to 2024, GWLs showed multi-scale periodic oscillations, with dominant periods of 50–64 months. GWLs in the red-bed region showed a continuous and slow decline, whereas those in the carbonate rock region remained relatively stable with a slight decreasing trend. Among the 13 hydrometeorological, geographic, and human activity factors, cropland area and precipitation had the strongest individual explanatory power. Their interactions with other factors produced nonlinear or bi-factor enhancement effects. The sustained expansion of cropland, together with declining precipitation, suggests that the observed phased and gradual decline in GWLs during 2019–2024 may be associated with a combined climate–human activity forcing mechanism. Annual GWL peaks were weakly and positively correlated with rainfall and temperature, while the lag between rainfall infiltration and GWL response varied with lithology. Full article

Field tests were conducted at a heterogeneous industrial site using one circulation well and six monitoring wells. Groundwater circulation well (GCW) extraction–injection (30 d), multi-component tracing (6 h), and circulation–oxidation (20 h) tests were performed to investigate the flow-field characteristics and their influence on multi-component solute transport. The results suggested that the extraction–injection circulation mode increased the flow rate of the single well from 0.5 m³/h to 3.5 m³/h, establishing a composite flow field with near-field circulation and far-field outward expansion. Short-term circulation achieved limited concentration attenuation primarily near the well with rebound. Long-term circulation elevated the average concentration attenuation rates of benzene from 13% in the short-term test to 61%, and chemical oxygen demand (COD) from 16% to 47%, expanding the remediation scope of the circulation well. Bromide tracer tests and an advection–dispersion equation characterized the heterogeneous flow field with preferential flow channels and slow migration zones. Furthermore, sulfate tracer transport was governed by adsorptive retardation and advective delivery. Circulation–oxidation tests showed that benzene and COD showed higher concentration attenuation than naphthalene. After cessation, benzene and COD concentration attenuation rates increased by 39% and 29% compared to the short-term test without oxidation. Electrical resistivity tomography (ERT) revealed the downward diffusion of the oxidant, suggesting that the circulation well system enhances oxidant transport and expands the oxidant-affected zone. This research provides field-scale diagnostic evidence and in situ diagnostic methodologies for GCW remediation at complex contaminated sites. Full article

Groundwater-storage anomalies (GWSA) derived from the Gravity Recovery and Climate Experiment (GRACE) mission provide valuable information for regional groundwater monitoring. Improving the spatial representation and temporal continuity of GRACE-derived GWSA is important for supporting groundwater assessment at subregional scales. A sequential framework combining Gaussian Process (GP) temporal gap filling and Random Forest (RF) spatial downscaling was developed for GWSA reconstruction in Henan Province, China, during 2002–2022. The GP model was used to reconstruct missing observations and characterize temporal variations, while the RF model statistically redistributed the GRACE-based GWSA signal using multi-source hydroclimatic predictors. The resulting dataset comprises model-derived GWSA estimates on a 1 km output grid constrained by the coarse spatial support of GRACE observations and the relationships learned from the auxiliary variables. Therefore, the 1 km grid spacing should not be interpreted as an independent 1 km resolving capability for groundwater-storage variations. Agreement with the parent GRACE-based GWSA product was used to assess coarse-scale reconstruction consistency rather than independent fine-scale accuracy. Comparison with groundwater-level anomalies from 63 monitoring wells yielded a correlation coefficient of 0.88, indicating temporal agreement at the sampled locations. Because the groundwater-level observations were not converted into storage anomalies using specific yield, this comparison does not establish absolute GWSA accuracy or independently validate the model-derived fine-scale spatial patterns. The reconstructed estimates revealed pronounced spatial heterogeneity in groundwater-storage changes, with persistent depletion concentrated in northern Henan, where groundwater decline rates exceeded 20 mm yr⁻¹. Overall, the framework improved the temporal continuity and spatial representation of GRACE-based groundwater-storage estimates while retaining the fundamental spatial constraints of satellite gravimetry. The results demonstrate the potential of integrating GRACE observations, machine learning, and multi-source Earth observation data to support regional groundwater assessment. Full article

Groundwater in Zhengzhou has experienced substantial changes under the combined effects of long-term abstraction, water-source substitution by the South-to-North Water Diversion Project, and ecological replenishment. During the 13th Five-Year Plan period, shallow and middle-deep groundwater levels in Zhengzhou recovered by 2.83 m and 6.46 m, respectively; nevertheless, extensive groundwater depression cones remained, highlighting the need for reliable groundwater burial-depth prediction to support dynamic monitoring and water-resource management. Aiming to address the limitations of the single long short-term memory (LSTM) network in groundwater burial depth prediction, including insufficient accuracy, tendency to fall into local optima, and difficulty in adaptive hyperparameter optimization, this study constructs a hybrid deep learning model (HO-LSTM-GPR). The Hippopotamus Optimization (HO) algorithm is employed to search for an appropriate parameter configuration of the LSTM network, and Gaussian Process Regression (GPR) is subsequently introduced to correct the residual deviations of the preliminary predictions. Four groundwater monitoring wells in Zhengzhou City, including the shallow wells Q1 and Q8 and the middle-deep wells Z14 and Z30, are selected to evaluate groundwater burial-depth prediction using historical input sequence lengths ranging from 1 to 30 days. The results show that the HO-LSTM-GPR model can significantly reduce prediction errors, and the Nash–Sutcliffe Efficiency (NSE) of all monitoring points exceeds 0.92, with the most prominent improvement observed at the Q1 site. The model can accurately characterize the high-frequency fluctuations of shallow groundwater levels and the slow variation characteristics of middle-deep groundwater levels, and effectively capture extreme points and mutation nodes. Within the comparison conducted in this study, the HO-LSTM-GPR model achieves higher fitting accuracy and prediction stability than the baseline LSTM model. Under the present dataset and model configuration, the HO-LSTM-GPR model achieves the best overall predictive performance when the historical input sequence length is 19 days. Overall, the HO-LSTM-GPR model exhibits relatively stable predictive performance for the investigated aquifers under different historical input sequence lengths. Full article

Climate change is altering global temperature and precipitation patterns, with particularly strong effects expected in Mediterranean regions, where reduced groundwater recharge and increased evapotranspiration may affect groundwater-dependent ecosystems. This study provides a preliminary, indicator-based assessment of the potential sensitivity of the Cabecera del Bornova Groundwater Body (Guadalajara, Spain), which sustains the Somolinos karst wetland, under natural conditions and protected as a Natural Groundwater Reserve and Natural Lacustrine Reserve. Empirical correlations were established between accumulated deviations of historical precipitation and observed piezometric levels in two monitoring piezometers using second-degree polynomial functions. The most informative relationships were obtained for piezometer ZE01, particularly at the daily scale, whereas the second piezometer showed weaker relationships. These functions were applied to regionalized climate projections generated with the FICLIMA methodology from ten CMIP6 models under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 scenarios from the IPCC Sixth Assessment Report. The results indicate a general decreasing tendency in empirical piezometric-level indicators throughout the 21st century, although the magnitude of the response is highly sensitive to the selected rainfall station, temporal resolution, climate model and scenario. Extreme projected declines are interpreted as extrapolation-sensitive outputs rather than deterministic predictions of aquifer drawdown or groundwater-reserve depletion. Direct impacts on lagoon level, spring discharge or wetland extent cannot be quantified with the dataset. The results highlight the need to expand piezometric monitoring, instrument the Manadero del Bornova spring, monitor lagoon water levels and develop physically based recharge and groundwater-flow models. Full article

At Yuehai Lake, China, managed Yellow River diversion maintains open water while imposing a persistent hydraulic boundary on the shallow aquifer. We combined water balance, zonal Darcy estimation, a calibrated regulated-stage groundwater model, particle tracking, major ions, and stable isotopes. Yellow River diversion supplied 93.7% of quantified external inflows. Zonal Darcy and model leakage were 2.39 and 2.47 × 10⁶ m³ a⁻¹. Across the monitored stage range (1105.96–1106.42 m), modeled leakage was 2.41–2.53 × 10⁶ m³ a⁻¹; alternative upper-aquifer structures produced 1.91–3.02 × 10⁶ m³ a⁻¹ without reversing exchange or eliminating the mound. Particles from 441 lakebed cells moved a median 24.5 m over 1065 d, indicating slow near-shore advection. Selected-screen isotopes were consistent with evaporatively enriched lake-water influence, whereas major ions showed a distinct west–east shift from Ca–Mg–HCO₃ toward Na–SO₄ and Na–Cl facies. Yuehai Lake therefore functions as a regulated losing lake. Its salinity pattern likely reflects lake leakage, agricultural return flow, soil-salt mobilization, background saline groundwater, and restricted drainage. Management should integrate lake-stage, groundwater-flow, and salinity monitoring. Full article

Arduino-based creepmeters utilizing a Linear Variable Differential Transformer (LVDT) and ultrasonic sensors were fabricated to monitor displacement changes along the creeping segment of the West Valley Fault (WVF) in southeastern Metro Manila, Philippines. Along with a custom-assembled, Arduino-based rain gauge, these instruments were initially intended to prevent data gaps during the COVID-19 pandemic when commercial data recorders experienced operational downtime. However, they have since proven to be cost-effective alternatives for determining short-term slip rates and monitoring displacement variations driven by episodic and seasonal precipitation changes. The LVDT creepmeter provides higher accuracy for displacement and slip rate determination. Conversely, the ultrasonic creepmeter is better suited for tracking abrupt displacement changes and, to some extent, longer-term displacement trends as it is more sensitive to environmental conditions. Deploying low-cost monitoring instruments in active fault regions bridges critical data gaps and improves the understanding of creep triggers and mechanisms. Although vertical creep occurs along pre-existing tectonic features of the WVF creeping segment, our creepmeter monitoring reveals sustained, accelerated creep within its southern portion. This localized movement is driven primarily by nontectonic forces—chiefly groundwater extraction, with episodic and seasonal precipitation influences. Consequently, this implies a continued ground rupture hazard and the potential for induced seismicity. Full article