The main aim of the present research is to assess the potential for soil liquefaction in the subsoil in twelve selected locations belonging to the Bogura Sadar area, using field-sponsored geotechnical data. This assessment utilizes the well-known, semi-empirical method developed by Seed and Idriss that considers earthquake magnitude, overburden pressure, the corrected value of SPT-N, peak ground acceleration (PGA), soil unit weight and depth of water table. The outcome is that, for a 6.5 MW earthquake, two zones have very high and seven zones have moderate susceptibility to liquefaction, and the remaining areas are less susceptible. The profiles of the factor of safety (FS) show that these values are greater than 1.0 at depths of 1.5 and 12 m for all the zones. However, at depths from 3 m to 9 m, most layers have FS values of less than or equal to 1.0, suggesting that the same seismic event may cause a liquefaction risk. In order to prevent or reduce this risk, surcharge loading is used as an efficient defensive action. The findings confirm that 400 kPa of surcharge guarantees to be on the safe side with respect to liquefaction in all considered zones. In general, the results contribute useful information for mitigating geotechnical hazards and realizing seismic resilience in the study region.

ABSTRACT The global phenomenon of water table rise (WTR) presents significant environmental challenges, particularly in arid and semi-arid regions lacking adequate stormwater infrastructure. In Oman, a prolonged WTR occurrence at Sultan Qaboos University (SQU) has raised concerns about subsurface and surface infrastructure stability. The imminent operation of Al-Jifnain dam is projected to intensify groundwater levels, increasing the risk of waterlogging that could affect building foundations, utilities, and vegetation. To assess the impact of seepage from the dam’s reservoir, a multi-scale groundwater–vadose zone modeling approach was applied. A 3D stratigraphic model of five hydrogeological units was constructed from 108 boreholes. Using MODFLOW-USG with a Smoothed Octree grid, the model was calibrated and validated. Results indicate groundwater mounding up to 4 m at the dam and 0.5 m–2 km downstream. HYDRUS2D simulations confirmed elevated waterlogging risks, compounded by the limited effectiveness of the cutoff wall and the inferred dissolution of caliche layers under increased freshwater infiltration.

Managing groundwater seepage around tunnels is critical to tunnel design, particularly when the tunnel is constructed below the water table. Accurate seepage flow patterns and water inflow prediction under ordinary and critical conditions are imperative to mitigate potential tunnel construction and service disasters. In the past, an in-depth study on the anisotropic hydraulic conductivity of the soil mass that may affect the seepage condition has not been carried out. In this work, this aspect has been investigated numerically for a rectangular tunnel submerged within a homogeneous sand mass, considering the anisotropic hydraulic conductivity ratio (kz / kx, kz = vertical hydraulic conductivity and kx = horizontal hydraulic conductivity) varying from 0.25 to 1. This study has presented the changes in the flow patterns of groundwater around a rectangular tunnel for different values of kz / kx, and the variation of water inflow rates along the crown, invert and walls of the tunnel. The results indicate that as kz / kx decreases from 1 to 0.25, the water inflow rate into the tunnel reduces linearly and the invert of the tunnel experiences the highest inflow rate. The total water inflow into the tunnel when kz / kx = 1 is three times the inflow rate for kz / kx = 0.25. An illustrative example has been included to help tunnel designers and construction engineers utilize the findings of this study for practical lining and permanent tunnel drainage systems.

The process of building data analytics systems, including big data systems, is currently being investigated from various perspectives that generally focus on specific aspects, such as data security or privacy, to the detriment of an engineering perspective on systems development. To address this limitation, our proposal focuses on developing analytics systems through a reuse-based approach, including stages ranging from problem definition to results analysis by identifying variations and building reusable, context-based assets. This study presents the reuse process by constructing two case studies that address the water table level prediction problem in two different contexts: the irrigated period and the non-irrigated period in the same study area. The objective of this study is to demonstrate the influence of context on the performance of widely used predictive models for this problem, including long short-term memory (LSTM), artificial neural networks (ANNs), and support vector machines (SVMs), as well as the potential for reusing the developed analytics system. Additionally, we applied the permutation feature importance (PFI) to determine the contribution of individual variables to the prediction. The results confirm that the same problem hypotheses yield different performance in each case in terms of coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), and mean square error (MSE). They also show that the best-performing predictive models differ for some of the hypotheses (ANN in one case and LSTM in another), supporting the assumption that context can influence model selection and performance. Reusing assets allows for more efficient evaluation of these alternatives during development time, resulting in analytics systems that are more closely aligned with reality, while also offering the advantages of software system composition.

Chaotic advection in regional groundwater flow under periodic water table fluctuations: An analytical model with depth-dependent aquifer properties

Sources and local factors influencing the effectiveness of implementing nutrient management practices for pollution control at the watershed scale.

Intensive flooding enhances methane but reduces carbon dioxide and nitrous oxide emissions in reservoir drawdown areas.

Assessment of groundwater vulnerability to heavy metals in four aquifers using machine learning algorithms.

Revealing the massive, often invisible, complexes of contemporary urban infrastructure that carry energy, communications, transport and water, urban disruption also exposes the social control of nature that is exercised through technology. At the same time, urban disruption is a sign of the world's vitality and its constant transformation. But what role does disruption play in making the territory more resilient? In Brussels, at the Marais Wiels, and in Rome, at the Lago Bullicante, bulldozers carrying out new land transactions remove the topsoil and reach the water table, which flows up and fills the excavations. Two new urban lakes have emerged in areas that were previously floodplains. These two disruptions are inhabited by multispecies ensembles, and the social learning that is essential for evolutionary resilience is routine here.

ABSTRACT Understanding water table (WT) variation is essential in peatland agriculture as the WT position is a major determinant of cultivation conditions and greenhouse gas emissions. To simulate past and future WT, we developed a sequential modelling approach by coupling two well-known models: HBV-light for cold climate hydrologic processes and MODFLOW for saturated subsurface flow conditions. We tested this approach in an agricultural peatland on Norway's west coast under two drainage configurations: a traditional pipe-drained field and an adjacent inverted peatland with a complex drainage system. In peat inversion, mineral soil excavated from below the peat is subsequently placed on top of the peat to form a protective cover layer aimed at reducing peat decomposition. Our modelling approach captured the daily WT dynamics of the fields between July 2022 and January 2025. The modelling results indicate that lateral flow dominates over the vertical flow in both drainage systems. Under future climate conditions between 2025 and 2100, the buried peat in the inverted peatland is expected to remain saturated for 25% of the time, whereas the peat in the pipe-drained field will be waterlogged rarely. Our modelling approach to simulate WT in managed peatlands can be set up relatively easily.

Abstract Groundwater is the primary freshwater resource in many of the world’s drylands, sustaining millions of people and supporting agriculture and ecosystems where surface water is scarce or unreliable. Recharge in these regions is highly episodic and occurs mainly through ephemeral streams (i.e., focused recharge), yet the mechanisms that determine whether surface flows contribute to aquifer replenishment remain poorly constrained. A common assumption is that large floods dominate recharge, but evidence from long-term monitoring is limited and inconclusive. We combine a unique hydrogeological monitoring dataset from the arid zone (Fowlers Gap in western New South Wales, Australia) with numerical modelling of vadose zone processes to assess the controls on focused groundwater recharge. Our results show that even extreme floods that overtopped piezometers did not produce measurable recharge at the water table. In contrast, significant recharge occurred only during a temporal cluster of moderate flow events in 2022. Numerical simulations confirm that temporal flow clustering produces longer periods of ephemeral streamflow, which progressively wet the vadose zone, overcome evapotranspiration-driven moisture deficits, and increase relative hydraulic conductivity, enabling percolation to the water table. Isolated floods, by contrast, largely saturate only shallow sediments and water is subsequently lost to evapotranspiration. By explicitly incorporating evapotranspiration, our modelling provides a more realistic representation of dryland recharge dynamics and highlights the roles of antecedent conditions and vadose zone properties. These findings demonstrate that recharge is not governed by rainfall totals or intensity alone, but critically depends on the timing and sequence of storm events. The implications for climate change assessments and water management are substantial, as projected shifts toward more intense but less frequent rainfall may reduce opportunities for clustering and thereby limit groundwater replenishment. Process-based modelling and event-scale analyses are therefore essential for reliable recharge projections and sustainable groundwater management in drylands.

ABSTRACT Questions have recently been raised about the suitability of using porewater samples collected with suction lysimeters to estimate per‐ and polyfluoroalkyl substances (PFAS) mass discharge in the vadose zone. Multiple lines of evidence were evaluated to determine if porewater samples collected during a data gaps investigation in the former fire training area (FFTA) at Ellsworth Air Force Base were reproducible and representative. Lines of evidence used include supplemental geologic and hydrogeologic data, which show the presence of a semi‐continuous silt/clay layer directly above the water table throughout much of the FFTA, and gravimetric moisture content results that demonstrate vertical water flow at a depth of 15 ft is substantially limited due to semi‐arid climatic conditions. Radial diagrams were used to visually demonstrate that there was negligible variability in porewater concentrations caused by varying sample yields in the deep zone. Additional lysimeters installed in the FFTA during the remedial investigation did not result in a significant difference in the estimated vertical mass discharge, which demonstrates that the number of lysimeter sampling points in this area is sufficient. Strong attenuation in PFAS soil concentrations with depth validates the order(s) of magnitude reduction between shallow and deep porewater concentrations observed near the former burn pit. Vadose zone PFAS mass discharge is shown to be 4%–19% of groundwater mass discharge below the water table for regulated constituents. Recommendations for field data collection and estimation of PFAS mass discharge in the vadose zone are presented.

Abstract Salinization of coastal aquifers is a current problem in many regions worldwide. Simulation of this process provides an important tool for the forecast of drinking water resources. The consideration of the unsaturated phreatic zone has an essential influence on the accuracy of the prediction. However, for the large temporal and spatial scales of the aquifers, the presence of the unsaturated subdomains creates challenging difficulties for the numerical methods. In this work, we investigate two approaches for simulating haline density-driven flow in partially saturated aquifers. The first approach, based on the Richards equation, uses a representation of the saturation field and employs an adaptive linearly implicit time discretization scheme. The second approach explicitly represents the water table using a level-set method and relies on weak coupling combined with a standard implicit Euler scheme. Both approaches employ a finite-volume discretization for spatial representation of fluid flow and salt transport. The implementation is based on the UG4 toolkit together with the parallel groundwater flow simulator d3f++. The resulting linear systems are solved using a geometric multigrid method. We compare the aforementioned approaches with respect to theoretical and numerical aspects. The performance of both methods is evaluated in three numerical experiments. In particular we demonstrate robustness of the linearly implicit scheme and introduce a stabilization for the level-set method. The high-performance computing (HPC) potential of the approaches is assessed and demonstrated as well.

Evaluation of sources and seasonal variations of dissolved 137Cs in stream water in forested catchments.

Abstract Permafrost soils contain approximately twice the amount of carbon as the atmosphere and this carbon could be released with Arctic warming, further impacting climate. Mosses are major component of Arctic tundra ecosystems, but the environmental drivers controlling heat penetration though the moss layer and into the soil and permafrost are still debated, especially at fine spatial scales where microtopography impacts both vegetation and soil moisture. This study measured soil temperature profiles (1-15cm), summer thaw depth, water table depth, soil moisture, and moss thickness at a fine spatial scale (2 m) together with meteorological variables to identify the most important controls on the development of the thaw depth during two Arctic summers. We found a negative relationship between the green moss thickness (up to 3 cm) and the soil temperatures at 15 cm, suggesting that mosses insulated the soil even at high volumetric water contents (>70%) in the top 5 cm. A drier top (2-3 cm) green moss layer better insulated deep (15 cm) soil layers by reducing soil thermal conductivity, even if the moss layers immediately below the top layer were saturated. The thickness of the top green moss layer had the strongest relationships with deeper soil temperatures, suggesting that the top layer had the most relevant role in regulating heat transfer into deeper soils. Further drying of the top green moss layer could better insulate the soil and prevent permafrost thawing, representing a negative feedback on climate warming, but damage or loss of the moss layer due to drought or fire could reduce its insulating effects and release carbon stored in the permafrost, representing a positive feedback to climate warming.

Impact of Holocene marine transgression and climatic changes on the Moros marsh (western Mediterranean, Spain).

Respiration modelling and CO2 budget assessment in the southern Baltic raised bog: Evaluating the impact of water table thresholds for ecosystem functioning

This study evaluates the spatial and seasonal dynamics of seawater ingress in the coastal phreatic aquifer systems of Kollam District, Kerala, using an integrated hydrochemical and index-based approach. A total of 21 groundwater samples were collected during the pre- and post-monsoon seasons of 2022 and analysed for major ions and physicochemical parameters. The Groundwater Quality Index for Seawater Mixing (GQISWI) was employed to identify salinization levels by integrating hydrochemical facies and chloride-derived mixing ratios. The Hill–Piper diagrams of the analysed water samples from the study area showed a shift, with samples transitioning from Na-Cl dominated facies during the pre-monsoon to Ca–HCO₃ type in the post-monsoon, indicating freshening of groundwater due to monsoon recharge. Similarly, the USSL diagram displayed a shift in several post-monsoon samples toward lower salinity zones, reflecting the dilution effect of rainfall. An inverse relation between depth to the water table and electrical conductivity was observed across coastal transects, with higher electrical conductivity observed in the shallow coastal zones and a decrease in conductivity with increasing depth towards the east. Despite the overall improvement in water quality during the post-monsoon season, a few localized zones continued to exhibit elevated salinity levels—likely attributable to limited aquifer thickness, proximity to the coastline/saline water bodies. The study demonstrates that monsoonal recharge plays a vital role in reversing salinity levels and provides a replicable framework for seawater ingress assessment and aquifer vulnerability mapping in coastal regions. Keywords: Kollam District, Seawater Ingress, Seasonal Salinity Dynamics, Coastal Phreatic Aquifer System, Hydrochemical Facies, Ground Water Quality Index

Abstract Studies integrating ichnology and sedimentology in paleoenvironmental interpretations are rare in Brazilian rift successions. This study applies an integrated ichno-sedimentological analysis to a well core from the Resende and Tremembé Formations (Cenozoic Taubaté Basin) to reconstruct paleoenvironmental conditions. Three paleoenvironments were identified: alluvial fan, braided river, and lacustrine. The alluvial settings is characterized by coarse-grained deposits displaying bioturbation intensity and sporadic trace fossils, dominated by Palaeophycus and Skolithos, reflecting opportunistic colonization. Braided river deposits consist of stacked sandstones with trough cross-bedding and a trace-fossil assemblage with Palaeophycus, Skolithos, Macanopsis, and Taenidium. The lacustrine environment is characterized by dark shale interbedded with fine-grained sandstones, including ostracod-rich white beds. Sparse beds containing Planolites indicate a complex lacustrine system with potential variations in salinity and oxygenation. Comparison with previous studies suggests that ichnofossils and paleosols reflect water table fluctuations and humid conditions in the Resende Formation. For the Tremembé Formation, ichnofossil data, palynomorphs (Botryococcus and Pediastrum), and taphonomic signatures in fishes suggest a dynamic environment with fluctuating water levels, periodic salinity increases, and decreased oxygen levels.

Origins and fate of polycyclic aromatic hydrocarbons (PAHs) in sustainable drainage systems (SuDS) in a Scottish urban area: Implications for groundwater systems.