Search Results (86)

Background/Objectives: In recent years, the discharge of antibiotics into rivers and irrigation canals has increased. However, few studies have addressed the impact of these compounds on agricultural fields that use such water to meet crop demands. Methods: In this study, the transport of two types of gentamicin (pure gentamicin and gentamicin sulfate) was modeled at concentrations of 150 and 300 μL/L, respectively, in a soil with more than 60 years of agricultural use. Infiltration tests under constant head conditions and gentamicin transport experiments were conducted in acrylic columns measuring 14 cm in length and 12.7 cm in diameter. The scaling parameters for the Richards equation were obtained from experimental data, while those for the advection–dispersion equation were estimated using inverse methods through a nonlinear optimization algorithm. In addition, a fractal-based model for saturated hydraulic conductivity was employed. Results: It was found that the dispersivity of gentamicin sulfate is 3.1 times higher than that of pure gentamicin. Based on the estimated parameters, two simulation scenarios were conducted: continuous application of gentamicin and soil flushing after antibiotic discharge. The results show that the transport velocity of gentamicin sulfate in the soil may have short-term consequences for the emergence of resistant microorganisms due to the destination of wastewater containing antibiotic residues. Conclusions: Finally, further research is needed to evaluate the impact of antibiotics on soil physical properties, as well as their effects on irrigated crops, animals that consume such water, and the soil microbiota. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Dredging of fine sediments and dumping of fines at disposal sites produce passive plumes behind the dredging equipment. Each type of dredging method has its own plume characteristics. All types of dredging operations create some form of turbidity (spillage of dredged materials) in the water column, depending on (i) the applied method (mechanical grab/backhoe, hydraulic suction dredging with/without overflow), (ii) the nature of the sediment bed, and (iii) the hydrodynamic conditions. A simple parameter to represent the spillage of dredged materials is the spill percentage (R_spill) of the initial load. In the case of cutter dredging and hopper dredging without overflow, sediment spillage is mostly low, with values in the range of 1% to 3%, The spill percentage is higher, in the range of 3% to 30%, for hopper dredging of mud with intensive overflow. Spilling of dredged materials also occurs at disposal sites. The spill percentage is generally low, with values in the range of 1% to 3%, if the load is dumped through bottom doors in deep water, creating a dynamic plume which descends rapidly to the bottom with cloud velocities of 1 m/s. The most accurate approach to study passive plume behavior is the application of a 3D model, which, however, is a major, time-consuming effort. A practical 1D plume dispersion model can help to identify the best parameter settings involved and to conduct fast scan studies. The proposed 1D model represents equations for dynamic plume behavior, as well as passive plume behavior including advection, diffusion and settling processes. Full article

Oil spills represent a critical environmental hazard with far-reaching ecological and economic consequences, necessitating the development of sophisticated modelling approaches to predict, monitor, and mitigate their impacts. This study presents a computationally efficient and physically grounded modelling framework for simulating oil spill drift in marine environments, developed using Python coding. The proposed model integrates core physical processes—advection, diffusion, and degradation—within a simplified partial differential equation system, employing an integrator for numerical simulation. Building on recent advances in marine pollution modelling, the study incorporates real-time oceanographic data, satellite-based remote sensing, and subsurface dispersion dynamics into an enriched version of the simulation. The research is structured in two phases: (1) the development of a minimalist Python model to validate fundamental oil transport behaviours, and (2) the implementation of a comprehensive, multi-layered simulation that includes NOAA ocean currents, 3D vertical mixing, and support for inland and chemical spill modelling. The results confirm the model’s ability to reproduce realistic oil spill trajectories, diffusion patterns, and biodegradation effects under variable environmental conditions. The proposed framework demonstrates strong potential for real-time decision support in oil spill response, coastal protection, and environmental policy-making. This paperwork contributes to the field by bridging theoretical modelling with practical response needs, offering a scalable and adaptable tool for marine pollution forecasting. Future extensions may incorporate deep learning algorithms and high-resolution sensor data to further enhance predictive accuracy and operational readiness. Full article

Longitudinal dispersion coefficient is a key parameter governing solute transport in porous media, with significant implications for various industrial processes. However, the impact of microfractures on the longitudinal dispersion coefficient remains insufficiently understood. In this study, pore-scale direct numerical simulations are performed to analyze solute transport in microfractured porous media during unstable miscible displacement. Spatiotemporal concentration profiles were fitted to the analytical solution of the convection–dispersion equation to quantify the longitudinal dispersion coefficient across different microfracture configurations. The results indicate that the longitudinal dispersion coefficient is highly sensitive to microfracture characteristics. Specifically, an increased projection length of microfractures in the flow direction and a reduced lateral projection length enhance longitudinal dispersion at the outlet. When Peclet number ≥1, the longitudinal dispersion coefficient follows a three-stage variation pattern along the flow direction, with microfracture connectivity and orientation dominating its scale sensitivity. Furthermore, both diffusion-dominated and mixed advective-diffusion regimes are observed. In diffusion-dominated regimes, significant channeling alters the applicability of traditional scaling laws, with the relationship between longitudinal dispersion coefficient and porosity holding only when the Peclet number is below 0.07. These results provide a comprehensive scale-up framework for CO₂ miscible flooding in unconventional reservoirs and CO₂ storage in saline aquifers, offering valuable insights for the numerical modeling of heterogeneous reservoir development. Full article

Numerical models are commonly used to support the management of diffuse pollution sources in large agricultural landscapes. This paper investigates the suitability of a three-dimensional groundwater streamline-based nonpoint source (NPS) assessment tool for agricultural aquifers. The streamline approach is built on the assumption of steady-state groundwater flow and neglects the effect of transverse dispersion but offers considerable computational efficiency. To test the practical applicability of these assumptions, two groundwater transport models were developed using the standard three-dimensional advection–dispersion equation (ADE): one with steady-state flow and the other with transient flow conditions. The streamline approach was compared with both ADE models, under various nitrate management practice scenarios. The results show that the streamline approach predictions are comparable to the steady-state ADE, but both steady-state methods tend to overestimate the concentrations across wells by up to 10% compared to the transient ADE. The prediction of long-term attenuation of nitrate under alternative land management scenarios is identical between the streamline and the transient ADE results. Full article

The movement of solutes in soil is crucial due to their potential to cause soil and groundwater pollution. In this study, a mathematical model based on the Advection Dispersion Equation (ADE) was developed to evaluate solutions for solute transport. This equation enabled us to attain a relationship for concentrations at different locations and times, also known as the breakthrough curve. Five columns (5 cm in diameter and 30 cm in height) of soil types were prepared to check the validity of the results. An evaluation of the calculated relations showed high accuracy in estimating the breakthrough curve and the saturated hydraulic conductivity of the soil. Full article

Water quality is intricately linked to the global water crisis since the availability of safe, clean water is essential for sustaining life and ensuring the well-being of communities worldwide. Pollutants such as industrial chemicals, agricultural runoff, and untreated sewage frequently enter rivers via surface runoff or direct discharges. This study provides an overview of the key mechanisms governing contaminant transport in rivers, with special attention to storage and hyporheic processes. The storage process conceptualizes a ubiquitous reactive boundary between the main channel (mobile zone) and its surrounding slower-flow areas (immobile zone). Research from the last five decades demonstrates the crucial role of storage and hyporheic zones in influencing solute residence time, nutrient cycling, and pollutant degradation. A review of solute transport models highlights significant advancements, including models like the transient storage model (TSM) and multirate mass transport (MRMT) model, which effectively capture complex storage zone dynamics and residence time distributions. However, more widely used models like the classical advection–dispersion equation (ADE) cannot hyporheic exchange, limiting their application in environments with significant storage contributions. Despite these advancements, challenges remain in accurately quantifying the relative contributions of storage zones to solute transport and degradation, especially in smaller streams dominated by hyporheic exchange. Future research should integrate detailed field observations with advanced numerical models to address these gaps and improve water quality predictions across diverse river systems. Full article

Monotonously stratified porous medium, where the layered medium changes its hydraulic conductivity with depth, is present in various systems like tilled soil and peat formation. In this study, the flow pattern within a monotonously stratified porous medium is explored by deriving a non-dimensional number, $F_{hp}$, from the macroscopic Darcian-based flow equation. The derived $F_{hp}$ theoretically classifies the flow equation to be hyperbolic or parabolic, according to the hydraulic head gradient length scale, and the hydraulic conductivity slope and mean. This flow classification is explored numerically, while its effect on the transport is explored by Lagrangian particle tracking (LPT). The numerical simulations show the transition from hyperbolic to parabolic flow, which manifests in the LPT transition from advective to dispersive transport. This classification is also applied to an interpolation of tilled soil from the literature, showing that, indeed, there is a transition in the transport. These results indicate that in a monotonously stratified porous medium, very low conducting (impervious) formations may still allow unexpected contamination leakage, specifically for the parabolic case. This classification of the $F_{hp}$ to the flow and transport pattern provides additional insight without solving the flow or transport equation only by knowing the hydraulic conductivity distribution. Full article

The fractional advection–dispersion equation is used in groundwater hydrology for modeling the movements of contaminants/solute particles along with flowing groundwater at the seepage velocity in porous media. This model is used for the prediction of the transport of nonreactive dissolved contaminants in groundwater. This paper establishes the existence and the uniqueness of solutions represented as fractional bi-variate power series of some initial-value problems and boundary-value problems for the fractional advection–dispersion equation. Moreover, a method to approximate the solutions using fractional polynomials in two variables and to evaluate the errors in a suitable rectangle is designed. Illustrative examples showing the applicability of the theoretical results are presented. Full article

The sustainable development of marine environments requires a deep understanding of their chemical and biological conditions. These are significantly impacted by the exchange of substances such as contaminants, heavy metals, and nutrients between marine sediments and the water column. Although the existing literature has addressed the physics of enhanced solute migration in sediment due to sea waves, the role of coupled flow and soil deformation has often been neglected. This study investigates the effects of wave-induced soil deformation on solute release from the marine sediment using a coupled numerical model that incorporates the effect of soil deformation into the advection–diffusion equation. The results reveal that solute release is notably accelerated in deformable sediments with a smaller shear modulus, with the longitudinal dispersion coefficient increasing up to five times as the shear modulus decreases from 10⁸ Pa to 10⁶ Pa. This enhancement is more pronounced in shallow sediments as the sediment permeability decreases, where the longitudinal dispersion coefficient in deformable sediments can be 15 times higher than that in non-deformable sediments at a hydraulic conductivity of 1 × 10⁻⁵ m/s. Furthermore, the rate of solute release increases with decreasing sediment saturation due to the compressibility of pore water, although this rate of increase gradually diminishes. Full article

Brazil has been one of the largest soybean producers in recent years. The soybean is a legume commonly found in family meals. Among the diseases affecting the grains, Asian soybean rust is one of the most concerning. The fungus causing the disease is spread by the wind, making it difficult to control. Although it has been researched since its first records, not much data are available regarding the macro propagation behavior of spores. Therefore, this research aimed to model its dispersion based on a partial differential equation, the diffusion–advection equation, used by researchers to model the behavior of any pollutant. The terms of this equation were developed from real data, processed by fuzzy logic, and the simulation results were compared with disease records throughout a harvest. By using this approach to model the spatiotemporal dynamics of this fungus, it was possible to simulate its spread satisfactorily. Additionally, its results were used as input variables for a fuzzy system that estimates the susceptibility of a given location to disease development. Full article

The advection–dispersion equation has been widely used to analyze the intermediate field mixing of pollutants in natural streams. The dispersion coefficient, manipulating the dispersion term of the advection–dispersion equation, is a crucial parameter in predicting the transport distance and contaminated area in the water body. In this study, the transverse dispersion coefficient was estimated using machine learning regression methods applied to oversampled datasets. Previous research datasets used for this estimation were biased toward width-to-depth ratio ($W/H$) values ≤ 50, potentially leading to inaccuracies in estimating the transverse dispersion coefficient for datasets with $W/H$ > 50. To address this issue, four oversampling techniques were employed to augment the dataset with $W/H$ > 50, thereby mitigating the dataset’s imbalance. The estimation results obtained from data resampling with nonlinear regression method demonstrated improved prediction accuracy compared to the pre-oversampling results. Notably, the combination of adaptive synthetic sampling (ADASYN) and eXtreme Gradient Boosting regression (XGBoost) exhibited improved accuracy compared to other combinations of oversampling techniques and nonlinear regression methods. Through the combined ADASYN–XGBoost approach, it is possible to enhance the transverse dispersion coefficient estimation performance using only two variables, $W/H$ and bed friction effects ($U/U^{*}$), without adding channel sinuosity; this represents the effects of secondary currents. Full article

Reaction fronts propagating in liquids separate reacted from unreacted fluid. These reactions may release heat, increasing the temperature of the propagating medium. As fronts propagate, they will induce density changes leading to convection. Exothermic fronts that propagate upward increase the temperature of the reacted fluid located underneath the front. For positive expansion coefficients, the warmer fluid will tend to rise due to buoyancy. In the opposite case, for fronts propagating downward with the warmer fluid on top, an unexpected thermally driven instability can also take place. In this work, we carry out a linear stability analysis introducing perturbations of fixed wavelength. We obtain a dispersion relation between the perturbation wave number and its growth rate. For either direction of propagation, we find that the front is stable for very short wavelengths, but is unstable for large enough wavelengths. We carry out a numerical solution of a cubic reaction–diffusion–advection equation coupled to Navier–Stokes hydrodynamics in a two-dimensional rectangular domain. We find transitions between the non-axisymmetric and axisymmetric fronts increasing with the width of the domain. Full article

The dispersion coefficients are crucial in understanding the spreading of pollutant clouds in river flows, particularly in the context of the depth-averaged two-dimensional (2D) advection–dispersion equation (ADE). Traditionally, the 2D stream-tube routing procedure (2D STRP) has been the predominant method for determining both the longitudinal and transverse dispersion coefficients of the 2D ADE under transient concentration conditions. This study aims to quantitatively analyze and address the limitations of the 2D STRP using hypothetically generated data. The findings of these evaluations revealed that the existing 2D STRP failed to accurately reproduce reliable results when the tracer clouds reached wall boundaries. This limitation prompted the development of the 2D STRP-i, which effectively resolves this drawback. The newly developed routing-based observation method, 2D STRP-i, enables the reliable estimation of dispersion coefficients, considering the effect of the wall boundary. The results indicated that the existing 2D STRP yielded 2D dispersion coefficients with relative errors ranging from 40% to 200%, while 2D STRP-i consistently yielded relative errors of 3% to 5% on average. When applied to tracer test data obtained through remote sensing, the 2D STRP-i demonstrated its ability to accurately observe temporal concentration distributions, even when wall boundaries have a significant impact on contaminant transport. Full article