Skeletonization, a crucial step in pore network modeling, traditionally involves the extraction of skeleton pixels from binarized, segmented X-ray images of porous materials. However, this conventional approach often suffers from user bias during segmentation, potentially leading to the loss of essential image details. This study addresses this limitation by developing deep learning model, called PoreSkel

Salt precipitation during brine evaporation in porous media is an important phenomenon in a variety of natural and engineering scenarios. This work establishes a multiphase multicomponent lattice Boltzmann (LB) method with phase change for simulating salt precipitation during brine evaporation. In the proposed LB models, the gas–brine multiphase flow, brine evaporation, salt concentration evolution

The hydrological cycle comprises several components, including precipitation, infiltration, evaporation, transpiration, and runoff, with the latter being a vital part of the cycle that connects precipitation to bodies of water. modelling is necessary due to limitations in standard hydrological measurement techniques, providing a better understanding of hydrological systems that were previously inaccessible

Previous studies of transverse hyporheic exchange in compound rivers mainly focused on processes driven by riverbed morphology, and neglected the effects of regional groundwater discharge (RGD). This study numerically investigated the transverse hyporheic exchange subjected to the joint influences of bedform and RGD in a conceptual compound channel. The results show the existence of an interfacial

Modeling dissolution processes in discrete fracture networks (DFNs) is a challenging task. Challenges are related to the highly nonlinear coupling between flow, mass transport, and reactive processes associated with fracture aperture evolution by dissolution. Further, advection-dominated transport due to fast fluid flow in fractures renders the problem more complex from a computational point of view

Ocean tides cause water table overheight near the seaward boundary of coastal aquifers which can have a large impact on groundwater flows and saltwater intrusion. Despite this, regional-scale coastal groundwater flow models often neglect the effects of ocean tides or alternatively assume that the influences of ocean tides and sea level are constant over time. These simplifications are often required

This paper expands the Consistent Particle Method (CPM) to simulation of turbidity currents with focus on turbulent water-sediment flow. A mixture model is adopted in solving the sediment transport equation to simulate the sediment mass transfer due to settling convection and turbulent diffusion. To compute the gravity-driven convection term, the proposed CPM-upwind scheme is relatively easy to implement

Surrogate modelling has been used successfully to alleviate the computational burden that results from high-fidelity numerical models of seawater intrusion in simulation-optimization routines. Nevertheless, little attention has been given to multi-fidelity modelling methods to address cases where only limited runs with computationally expensive seawater intrusion models are considered affordable imposing

The geomorphic relations of hydraulic geometry at-a-station and downstream, expressed as power laws, are derived for a straight, single thread, gravel river channel. The cross-section has a plane central bed, narrow or wide, flanked by curved sides or banks. The analysis employs mechanistic formulae for fixed and mobile bed flow resistance, downchannel bedslope, bedload transport and the novel introduction

In the context of a T-shaped open-channel confluence, where the tributary flow separates at the downstream junction edge and creates a separation zone in the post-confluence channel, this paper provides a critical reflection upon the terminology and the delineation methods for the separation zone and its proxies: the recirculation zone and the reverse flow zone. Following the fluid-mechanical literature

As a gridless computational method, physics-informed neural networks (PINNs) have been widely applied and are a research hotspot in the field of numerical simulation due to their potential to provide approximations that are infinitely close to the analytical solutions. To address the complex hydrodynamic simulation scenarios with a large solution domain, where the conventional PINNs are not fully applicable

The connectivity of the more conductive hydrofacies strongly determines flow and transport in heterogeneous media. Here we study solute transport in 3D binary isotropic samples with a proportion p of a high hydraulic conductivity facies (k+), and (1−p) of a low (k−) one. The k+ facies is characterized by two connectivity parameters: a connectivity structure type (no, low, intermediate and high), that

Even though the original paper (Townley, 1995) contained no significant mathematical errors, this Addendum has been prepared (i) to give readers access to 3D graphics that are of much higher quality than are available online, (ii) to provide access to Mathematica notebook files in both .nb and .pdf formats, that demonstrate the use of Mathematica to obtain the six published solutions and to produce

The direct acquisition of the permeability of porous media by digital images helps to enhance our understanding of and facilitate research into the problem of subsurface flow. A complex pore space makes the numerical simulation methods used to calculate the permeability quite time-consuming. Deep learning models represented by three-dimensional convolutional neural networks (3D CNNs), as a promising

Steady, phreatic flows in wedge-shaped aquifers subtended by a tilted bedrock and discharged through a hillslope seepage face are studied by 2-D and 1-D analytical models for fully saturated and a FEM numerical model for saturated-unsaturated flows. The curvilinear triangle in the hodograph domain is conformally mapped onto a reference half-plane where the Hilbert problem is solved for two holomorphic

Sediments with poor drainage conditions are prone to build-up of excess pore water pressure when exposed to dynamic wave loading. This results in accumulated seepage flow that may have a significant impact on migration of solutes in marine sediments. In this study, the complex interplay between solute transport and wave-induced seepage process is investigated through a pioneering approach that combines

We investigated the applicability of Silica encapsulated, superparamagnetic DNA particles (SiDNAmag) in determining aquifer hydraulic parameters at different ionic strengths (1 mM, 5 mM, and 20 mM phosphate buffer) of injection suspension. Thereto, in a homogeneous, unconsolidated sand tank we pulse - injected two uniquely sequenced SiDNAmag at two injection points. At 0.5 m and 0.8 m downstream from

This study develops two new analytical models for radially divergent tracer tests at a fully-penetrating well in two-zone confined aquifers of skin and formation zones. Mixing length in the well is below the well length for inducing vertical dispersion. One model treats skins as an adsorptive Robin boundary condition for reflecting the adsorption effect. The other model applies skin's governing equation

In this study, a novel algorithm coupling the flow at the pore and representative elementary volume (REV) scales was developed to analyze the effect of microbial growth at the pore scale on the permeability decay of porous media at the REV scale. This provides a new method for investigating microbial clogging in porous media. At the pore scale, an immersed boundary-lattice Boltzmann model was used

Shallow groundwater resources overlaying deep saline formations used in carbon storage applications are subjected to a potential contamination threat by CO2/brine leakage via natural or anthropogenically-induced conductive pathways in the confining caprock. Identifying the leakage source location and rate is critical for developing remediation plans and designing corrective actions. Owing to limited

We propose a novel hybrid-dimensional model for the Darcy–Forchheimer flow in fractured rigid porous media, with a natural applicability to non-conforming meshes. Motivated by the previous work on the reinterpreted discrete fracture model (RDFM) for Darcy flows, we extend its key idea to non-Darcy flows. Coupling the Darcy’s law in the matrix and the Forchheimer’s law in the fractures through the introduction

Multi-species diffusion/heterogeneous reaction coupled problem in porous media involving a boundary layer problem is studied. The spectral approach developed in our previous work allows to derive a macroscopic model in the high Damköhler number regime combining homogenization technique and spectral approach. Such a homogenized model cannot describe the perturbation at the external boundary where the

Decision support systems (DSSs) in water resources management often use optimization models to make decisions. Therefore, the quality of these models is crucial for the success of DSSs. However, optimization models can struggle with reaching global optima, resulting in inconsistent and untrustworthy results for decision-makers. Additionally, current solution methods can be slow and inefficient, hindering

A decrease in reservoir pressure can lead to remobilization of residually trapped CO2. In this study, the pore-scale processes related to trapped CO2 remobilization under pressure depletion were investigated with the use of high-resolution 3D X-ray microtomography. The distribution of CO2 in the pore space of Bentheimer sandstone was measured after waterflooding at a fluid pressure of 10 MPa, and then

In this paper we use a statistical framework to analyze the relation between storm properties and the statistics of extreme precipitation. We identify storm events using a 24-hour dry hiatus separation. We investigate the statistics of the hourly maximum intensity for the heaviest storm events at durations of 1 and 24 h. A two-parameter Weibull distribution is used to represent precipitation frequencies

Miscible density-driven convection in porous media has important implications to the long-term security of geological carbon sequestration. Laboratory investigations of miscible density-driven convection in heterogeneous porous media have been greatly limited due to the challenge in constructing well-controlled heterogeneous permeability fields. In this study, three-dimensional (3D) printing was used

CO2 sequestration and storage in deep saline aquifers is a promising technology for mitigating the excessive concentration of the greenhouse gas in the atmosphere. However, accurately predicting the migration of CO2 plumes requires complex multi-physics-based numerical simulation approaches, which are prohibitively expensive due to highly nonlinear coupled governing equations and uncertainties in heterogeneous

Per- and polyfluoroalkyl substances (PFASs) have become emerging contaminants of critical concern. Comprehensive understanding of the transport and fate of PFAS in the vadose-zone, a type of water-unsaturated porous media, is key to determination of the risks of the PFAS contamination in the subsurface and to the development of the effective remediation strategies. Accurate modeling of the PFAS transport

In dam-break problems, two-dimensional (2D) models on the vertical plane appropriately capture the non-hydrostatic pressure distribution but with a high computational cost. This study presents a hybrid Lagrangian solver of one-dimensional (1D) shallow water flow and a 2D large-eddy simulation with a sub-particle scale to simulate dam-break flows over frictional beds. The proposed 1D-2D hybrid scheme

The heat extraction efficiency, storage, and safety of carbon dioxide (CO2) sequestration and methane (CH4) injection/post-production in naturally fractured formations have attracted significant interest. However, these studies require the examination of complex thermal-hydraulic-mechanical (THM) interacting processes, which include muti-discipline coupling and phase changes. Energy transfer mechanisms

Recent advances in remote sensing technologies along with the increased availability of topographic data have lately encouraged the development of automatic DEM (Digital Elevation Model)-based procedures for floodplain delineation. Geomorphic methods, establishing relationships between flood descriptors and morphologic catchment characteristics, appear particularly suitable to be implemented within

Enhanced water management systems depend on accurate estimation of subsurface hydraulic properties. However, geologic formations can vary significantly, so information from a single source (e.g., widely spaced boreholes) is insufficient in characterizing subsurface aquifer properties. Therefore, multiple sources of information are needed to complement the hydrogeology understanding of a region. This

Interactions between the tide and sloping sea boundary make watertable fluctuations in coastal unconfined aquifers complicated. Based on a perturbation method, we derived a new analytical solution to predict watertable fluctuations for coastal unconfined aquifers with a sloping sea boundary. Following validation with a numerical model, the analytical solution was used to explore the effects of the

In August 2019, this journal published the paper “Water sorptivity of unsaturated fractured sandstone: Fractal modeling and neutron radiography experiment”, which reports on the experimental monitoring and analytical calculation of capillary moisture absorption in fractured sandstone. This discussion, considered a post-publication review, raises a number of concerns in relation to this paper. These

This study introduces firm information gain for model discrimination based on Shannon entropy and worst-case scenario experimental design. Firm information gain is the minimal additional information gained by an experimental design with respect to existing information. Robust experimental design aims to maximize the firm information gain by searching for the least number of new pumping wells and observation

A hydrological model incurs three types of uncertainties: measurement, structural and parametric uncertainty. For instance, in rainfall-runoff models, measurement uncertainty exists due to errors in measurements of rainfall and streamflow data. Structural uncertainty exists due to errors in mathematical representation of hydrological processes. Parametric uncertainty is a consequence of our inability

Reservoir management and contaminant transport simulations rely on accurate modeling of the subsurface. This task becomes more challenging when the reservoir of interest also has a large amount of fractures. Inverse modeling of these fractured media involves first performing multiple field tests such as pumping tests, tracer tests, or seismic surveys. Inverse modeling methods then are used to find

Although the fluid invasion process impacts the transport and dispersion of chemicals and contaminants in the resident phase of natural, manufactured, and biological unsaturated porous media, these effects remain poorly understood. In this study, we investigate the role of hydrodynamic dispersion in different invasion patterns within the resident phase. While nonidealities in pore structures contribute

Low-permeability aquitards are important sedimentary units that protect the underlying confined aquifers from contamination by seawater and anthropogenic sources in coastal leaky aquifer systems. Therefore, the integrity of the aquitard is of crucial importance. However, the aquitard integrity may be vulnerable to horizontal heterogeneities in the form of aquitard windows. In this study, an innovative

The stable isotopic signature of xylem water differs from those of rainfall and river water. Without considering the water exchange through the vapor phase, this phenomenon implies that when the event water (new water) infiltrates the soil, a part of the pre-event water (old water) is isolated. The isolation and immobilization of old water are suspected because of the low matrix potential. Because

In this paper, we propose a new approach to simultaneously map the fracture/conduit network and the equivalent transmissivity of the rock matrix from hydraulic head measurements acquired during pumping/injection tests in fractured aquifers. The algorithm relies on the use of a multitask neural network to directly approximate the joint inversion operator that links hydraulic head data to aquifer hydraulic

Managed aquifer recharge (MAR) techniques are in demand to cope with water scarcity challenges posed by climate change and groundwater overexploitation. One of the long-lasting technical issues associated with MAR systems is physical clogging. The intrusion and deposition of external fines during water recharge reduce the infiltration capacity of the site over time. Operation and maintenance (O&M)

Knowledge of freezing–thawing (F–T) cycles of sulfate saline soil is crucial regarding the spatial–temporal distribution of solutes in the soil, soil salinization, and cold region engineering in sulfate saline soil areas. F–T tests of saturated sulfate saline soils with different salt contents, water supply conditions, and the number of F–T cycles were conducted. The coupling mechanism of water and

The nonstationary hydrological frequency analysis (NS-HFA) aids in assessing the recurrence of hydrological extremes under nonstationarity, but its reliability is often questioned due to relatively limited record lengths. The Metastatistical extreme value (MEV) distribution, which harnesses the ordinary event records along with the extremes, has proven advantageous under stationarity and in instances

In this paper, the authors propose a new approach to solving the groundwater flow equation in the Toth basin of arbitrary top and bottom topographies using deep learning. Instead of using traditional numerical solvers, they use a DeepONet to produce the boundary-to-solution mapping. This mapping takes the geometry of the physical domain along with the boundary conditions as inputs to output the steady

The statistical characterization of precipitation (P) at short durations (≤ 24 h) is crucial for practical and scientific applications. Here, we advance the knowledge of and ability to model the space-time correlation structure (STCS) and marginal distribution of short-duration P using a network of rain gages in central Arizona with one of the largest densities and spatial coverages in the world. We

A deep learning technique called Physics Informed Neural Networks (PINNs) is adapted to study steady groundwater flow in unconfined aquifers. This technique utilizes information from underlying physics represented in the form of partial differential equations (PDEs) alongside data obtained from physical observations. In this work, we consider the Dupuit–Boussinesq equation, which is based on the Dupuit–Forchheimer

Recent studies have emphasized the importance of nonlocal models in characterizing bedload transport in natural rivers, particularly in mixed-size gravel beds or steep hillslopes. Nonlocality denotes that a quantity (flux) at a specific location x is dependent on the conditions in the surrounding area, as opposed to solely at the location itself. This concept applies in bedload transport even in planar

Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data (e.g.,

Watersheds act as low-pass filters, damping and attenuating climatic signals as water moves through the surface and subsurface. This is a well observed phenomenon; however, the ways in which watershed properties control the nature of this filtering are less well documented, especially with respect to groundwater surface water interactions. Here, we use a physically based groundwater surface water model