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• An upscaling framework is proposed to predict dispersivity in natural fracture. • Geostatistical analysis of the fracture aperture is implemented. • The upscaling dispersivities of the fracture core samples are predicted. Fluid flow and mass transport parameters are greatly impacted by the fracture surface's heterogeneous properties. By quantifying the spatial correlation patterns of fracture apertures, this study intends to establish an upscaling framework utilizing Lagrangian-based transport models to estimate dispersivities of naturally fractured granite cores. To do this, the surface morphology of the fragmented core sample was photographed using a 3D laser profile scanner with varied degrees of accuracy. Following a geostatistical analysis of the fracture aperture data, common covariance models were fitted to determine the integral scale of log fracture aperture. This information was used to estimate dispersivity using the Lagrangian-based transport models, which only required the collection of fractured geostatistical data. The study also assessed how the dispersivities are affected by fracture lengths and the measurement accuracy of aperture data in this model. The findings showed that the fracture aperture spatial bivariate correlation structures follow the exponential covariance model. Additionally, while the variance of log fracture apertures is significantly influenced by both the data resolutions and the core samples themselves, the integral scale of log fracture apertures primarily depends on the length of the fracture. In terms of the fracture length, the upscaled dispersivities range from 2.35% to 7.21%. The development of upscaling techniques for estimating dispersivities in fractured and heterogenous granitic rocks and scaling them up to the field size for the accurate prediction of solute transport mechanisms can be guided by these findings. [ABSTRACT FROM AUTHOR]

• Two simplified methods are proposed based on t p and t a to estimate the regional groundwater flow velocity, effective porosity and dispersivity; • Compared with previous methods, the t a method takes the chase phase into account which is important to minimize the impact of well skins and wellbore storage on the shape of BTCs; • Compared with traditional curve-fitting methods, the t p and t a methods require fewer observation data and do not require any optimization algorithms, thus avoiding the problem of falling into local optimum. The single-well push–pull (SWPP) test has been widely used for several applications, including determination of transport parameters such as regional groundwater flux velocity, effective porosity and dispersivity. A complete SWPP test usually includes four phases of injection, chase, rest, and extraction, while previous models mostly ignore the chase phase for the sake of simplification. Actually, the chase phase is important to minimize the impact of well skins and wellbore storage on the shape of the breakthrough curves (BTCs), thus is necessary and should be included in the model. To this end, two simplified methods are proposed in this study based on two different time t p and t a during a four-phase SWPP test to estimate the parameters related to transport, where t p and t a correspond to the time of the peak concentration during the injection phase and the time when the center of tracer mass returns to the wellbore during the extraction phase, respectively. Specifically, the t p method can be used to estimate the regional groundwater flow velocity and dispersivity (transverse and longitudinal), while the t a method is used to estimate the regional groundwater flow velocity and the effective porosity. Finite-element numerical modeling of the SWPP test based on the coupling of two-dimensional transient groundwater flow and solute transport is employed to test the applicability of the proposed methods. Results indicate that both the t p and t a methods proposed in this study perform satisfactorily in estimation of regional groundwater flow velocity, effective porosity and dispersivity, and these two methods require fewer observations than traditional curve fitting methods and do not require any optimization algorithms. We have also compared the proposed two methods with several previous methods, and conclude that these two new methods generally perform better than those of previous studies in terms of parameter estimation reliability. [ABSTRACT FROM AUTHOR]

Highlights • Constraining the 3D variable density numerical model with field measurements. • Estimation of anisotropic heterogeneous hydraulic conductivity. • A novel method to validate solute concentration results with ERT profile. • Verification of assigned aquifer topography and estimated geological formation. Abstract The solution for the inverse problem of seawater intrusion at an aquifer scale has not been studied as extensively as forward modeling, because of the conceptual and computational difficulties involved. A three-dimensional variable-density conceptual phreatic model is developed by constraining with real-field data such as layering, aquifer bottom topography and appropriate initial conditions. The initial aquifer parameters are layered heterogeneous and spatially homogeneous that are based on discrete field measurements. The developed conceptual model shows poor correlation with observed state variables (hydraulic head and solute concentration), signifying the importance of spatial heterogeneity in hydraulic conductivity and dispersivity of all the layers. The conceptual model is inverted to estimate the anisotropic spatially varying hydraulic conductivity and the longitudinal dispersivity at the pilot points by minimizing the least square error of state variables across the observation wells. The inverse calibrated model is validated for the hydraulic head at validation wells and the solute concentration is validated with equivalent solute concentration derived from the electrical resistivity, which shows good results against the field measurements. The verification of estimated anisotropic hydraulic conductivity with the electrical resistivity tomography image shows good agreement. This investigation gives an insight about constraining the highly parameterized inverse model with real-field data to estimate spatially varying aquifer parameters for an effective simulation of the seawater intrusion in a layered coastal aquifer. [ABSTRACT FROM AUTHOR]

[Display omitted] • Graphene is tested as soil improver and compared with classical ones. • Graphene changes dispersivity and specific retention in sandy soils. • Graphene did not alter hydraulic conductivity, total and effective porosity. • Graphene allowed a faster heat transfer in the soil. In this study, for the first time, the changes in relevant hydraulic parameters (e.g., hydraulic conductivity, effective porosity, and dispersivity) induced by the introduction of graphene in a calcareous sandy soil and a siliciclastic riverine soil were monitored and modelled via leaching column experiments. Column experiments were also run with traditional soil improvers (compost, biochar, and zeolite) to compare the changes induced by graphene versus well-studied soil improvers. Constant pressure head tests were used to calculate the hydraulic conductivity of each column, while leaching experiments were run to estimate porosity and specific retention, and for each treatment three replicates were done. Columns were then run in saturated conditions via a low flow peristaltic pump and monitored for electrical conductivity, temperature, and chloride. CXTFIT 2.0 was employed to inversely model the column experiments and retrieve parameters like effective porosity, longitudinal dispersivity, bulk thermal diffusivity, and thermal retardation factor. Results highlighted small changes of hydraulic conductivity, porosity, and effective porosity induced by graphene addition (as well as by the other soil improvers) for both soils. A marked increase (nearly 20 %) of specific retention values was instead recorded in the amended columns with respect to control ones. Chloride breakthrough curves modelling showed that graphene doubled dispersivity in the calcareous sandy soil (5.82 ± 1.4 cm) compared to the control (2.6 ± 0.29 cm), while it halved dispersivity in the siliciclastic riverine soil (0.31 ± 0.05 cm) with respect to the control (0.65 ± 0.06 cm). Thermal retardation factors were decreased by graphene by approximately 20 % for both soils. The model fitting via TDS (derived from the electrical conductivity monitoring) produced unreliable dispersivity values in most of the experiments due to the nonconservative nature of this parameter compared to chloride. The results highlight that graphene affected dispersivity but did not significantly alter other physical parameters relevant for solutes transport in sandy soils in comparison to classical improvers, thus future studies should focus on the graphene's effects on nutrients and agrochemicals leaching in unsaturated flow conditions. [ABSTRACT FROM AUTHOR]

Summary Usually electrolytic tracers are employed for subsurface characterization, but the interpretation of tracer test data collected by low cost techniques, such as electrical conductivity logging, can be biased by cation exchange reactions. To characterize the aquifer transport properties a saline and heat forced gradient test was employed. The field site, located near Ferrara (Northern Italy), is a well characterized site, which covers an area of 200 m 2 and is equipped with a grid of 13 monitoring wells. A two-well (injection and pumping) system was employed to perform the forced gradient test and a straddle packer was installed in the injection well to avoid in-well artificial mixing. The contemporary continuous monitor of hydraulic head, electrical conductivity and temperature within the wells permitted to obtain a robust dataset, which was then used to accurately simulate injection conditions, to calibrate a 3D transient flow and transport model and to obtain aquifer properties at small scale. The transient groundwater flow and solute-heat transport model was built using SEAWAT. The result significance was further investigated by comparing the results with already published column experiments and a natural gradient tracer test performed in the same field. The test procedure shown here can provide a fast and low cost technique to characterize coarse grain aquifer properties, although some limitations can be highlighted, such as the small value of the dispersion coefficient compared to values obtained by natural gradient tracer test, or the fast depletion of heat signal due to high thermal diffusivity. [ABSTRACT FROM AUTHOR]

Highlights: [•] Hydrodynamic parameters of oil-contaminated sand are investigated and calibrated. [•] The effective porosity of sand is inversely proportional to the residual oil saturation. [•] The permeability of sand decreases exponentially with increasing residual oil saturation. [•] A positive correlation is observed between dispersivity and residual oil saturation. [Copyright &y& Elsevier]

Highlights: [•] A transport model is developed for interpretation of tracer test data. [•] Dispersivity can be predicted from derivative analysis of tracer test data. [•] Rock matrix block size distribution can be predicted using the developed model. [ABSTRACT FROM AUTHOR]

Highlights: [•] A lumped mass transfer coefficient is obtained for transport in fractured aquifers. [•] The mass transfer coefficient is obtained for various geometries. [•] The mass transfer coefficient is a function of scale and injection rate. [•] Field scale simulation without including dispersion in fracture is not valid. [•] Ignoring dispersion in modeling a lab test may be valid at high injection rates. [ABSTRACT FROM AUTHOR]

Summary: In this study, previous interpretations of the density-dependent flow and transport processes induced by pumping freshwater above denser saltwater in four laboratory sand-tank experiments are extended using numerical modelling. The numerical model captured the transition in dispersiveness of up-coning plumes observed in the laboratory (i.e. highly dispersive at early times tending to sharp-interfaces after saltwater reaches the well). This demonstrates the applicability of the velocity-dependent dispersion of the modelling code. In all four experiments, head-dependent flux boundary conditions were used to simulate the sand-tank side boundary conditions. The experimentally derived boundary conductance values indicate non-linear variations in the resistance to flow through side inflow ports between the different experiments. Nonetheless, linear boundary head-inflow relationships adequately reproduced laboratory up-coning. The numerical model was able to reproduce the laboratory results within a reasonable level of accuracy and with minimal calibration of model parameters for three of the four experiments. This serves to validate those particular laboratory observations. The “double-peak” up-coning observed late in the fourth laboratory experiment was not reproduced by the model. Further analysis considering adsorption of the Rhodamine tracer is suggested to explore the cause of this effect. Numerical modelling results were compared to an existing sharp-interface analytical solution, which corresponded well with the numerical modelling results for early stages of the four up-coning experiments, despite the dominant influence of dispersion at early times. [Copyright &y& Elsevier]

Summary: A simple method and an optimization method for explicit estimation of specific dispersivity and injected mass from an ideal breakthrough curve (BTC) due to an instantaneous injection of a solute are proposed. The specific dispersivity is defined as dispersivity divided by the distance between the injection and sampling points. An estimate of the injected mass is the pollution load from a point source. The proposed simple method yields successive estimates of the specific dispersivity and injected mass as additional data become available, which identifies the time after which the test may be terminated as the collection of data beyond this time would not improve the estimates. Using this method, the data for different flow rates and injected masses can be analyzed simultaneously. The proposed simple method does not require the full BTC to be observed. The proposed optimization method uses a derivative based technique in which the analytical derivatives are derived. The optimization method is applicable for any value of specific dispersivity. [Copyright &y& Elsevier]

Tracer tests have been performed on a 3D tank of dimensions 560×100×100 cm3. These experiments at laboratory scale are used to define effective hydraulic conductivity and macrodispersivity. The tracer tests have been performed on two kinds of heterogeneous porous material: a channel structured medium, with channels crossing the whole tank, and a statistically correlated random structure. The statistically correlated field was first established by a sequential type generator with a prescribed exponential covariance. The theoretical random field is then modified according to the available sand hydraulic conductivities. The obtained LnK variance is 1.03 and the integral scale 23.1 cm.Results obtained concerning the channel structured media show that it behaves like a stratified medium from an hydrodynamical and mass transfer point of view. The effective hydraulic conductivity is equal to the arithmetic mean and the variance of the concentration is proportional to t2, t being the mean travel time of the tracer displacement..For the correlated random field, the effective hydraulic conductivity falls between by the geometric and the arithmetic mean. No match with theoretical values have been found because the boundary conditions effects cannot be neglected due to the dimension of the tank compared to the integral scale. Similar conclusions have been obtained for macrodispersivity. The tracer tests could be simulated by a 1D advection–dispersion equation but with a significant higher macrodispersivity than predicted by stochastic theories for infinite media. [Copyright &y& Elsevier]

• Solute transport dynamics were studied under different water table conditions. • Mobile-immobile model was the most suitable to describe solute transport. • The mobile water fraction changed according to different water table managements. • A shallow water table enhanced the macropore network > 327 µm. • Preferential solute transport is enhanced by the occurrence of a shallow water table. A shallow water table might enhance preferential solute movement by modifying both the water flow and solute dynamics. In this study, we estimated soil hydraulic and solute transport parameters through a tracer experiment in lysimeters comparing different water table levels. In a set-up of 12 lysimeters, the bottom boundary condition was set as a water table depth of 120 cm, or 60 cm, or as free drainage. A tracer solution of bromide (250 mg l−1, 40 mm) was added to each lysimeter and soil water was sampled with suction cups at different depths for the following 174 days. Soil water content and matric potential were monitored using TDR probes and electronic tensiometers at the same depths. Soil hydraulic and solute transport parameters in different soil layers were estimated by inverse modeling using HYDRUS 1D. Soil hydraulic parameters were estimated from the Mualem-van Genuchten equations, while both the advection–dispersion (ADE) and physical non-equilibrium mobile-immobile water (MIM) models were used to describe the solute transport. Moreover, the soil pore network was analyzed by means of 3D X-ray microtomography. Results showed different solute dynamics between contrasting water table managements. With free drainage, solute in the immobile domain was negligible, and its transport was fully associated with the mobile water flow. In contrast, a shallow water table affected the tracer transport, by modifying a) the soil pore network, with an increase of the macropores and a reduction of the pore connectivity; b) the flow field, with an increase of immobile water and a reduction of α MIM , indicating slow exchange between mobile and immobile regions, in turn promoting preferential pathways. Hence, groundwater pollution might be worsened by preferential solute transport of agrochemicals occurring with shallow water table conditions. [ABSTRACT FROM AUTHOR]

• Column experiments were carried out to explore the effects of saturation and particle size on the solute dispersivity. • A clear non-monotonic relationship was found between the dispersivity and soil water saturation. • The extent of non-monotonicity was more pronounced for relatively coarse-textured soils, but less for finer soils. A major contaminant transport process in soils is hydrodynamic dispersion by affecting the spreading and arrival of surface-applied pollutants at underlying groundwater reservoirs. When a soil is unsaturated, hydrodynamic dispersion is very much affected by soil water saturation. Centimeter- and decimeter-scale column experiments were carried out to explore the effects of fluid saturation and particle size on the unsaturated solute dispersivity. Measured in-situ breakthrough curves were analyzed in terms of both classical advection–dispersion and dual-porosity (mobile-immobile) type transport equations. A clear non-monotonic relationship was found between the dispersivity and soil water saturation. The extent of non-monotonicity was more pronounced for a relatively coarse-textured sand compared to a finer sand. This finding has been reported rarely before; it explains some of the inconsistencies of saturation-dispersivity relationships in the literature. [ABSTRACT FROM AUTHOR]

• Microbial growth increased spatially averaged dispersivity by a ratio of 1.67. • Biomass and gas increased spatially averaged dispersivity by a ratio of 2.46. • Some hydrodynamic parameter models to estimate dispersivity were evaluated. • Biofilm and biogenic gas induced insignificant change in dispersivity during anaerobic biodegradation. Bioremediation of groundwater is a widely applied method for remediation of contaminated groundwater. Microbial growth and biogenic gas accumulation are common during anaerobic bioremediation. These two processes can alter groundwater flow patterns and affect the ability to deliver electron donors or acceptors to target zones through changes in subsurface permeability, porosity, and dispersivity. In this study we analyzed three tracer tests conducted in an anaerobic two-dimensional sand-filled cell inoculated with a methanogenic culture. The ability of models to predict changes in porosity, permeability, and dispersivity during microbial growth and methane generation were evaluated. Microbial growth increased spatially averaged dispersivity by a ratio of 1.67. Biomass growth coupled with biogenic gas increased the spatially averaged dispersivity by a ratio of 2.46. In contrast with biomass measurements from confocal laser scanning microscopy, the model of Taylor and Jaffe (1990b) predicted a dispersivity increase by a factor of 10–1300. For water saturations greater than 0.5, the model of Sato et al. (2003) provided estimates of the effect of gas on dispersivity similar to values fit from modelling of the tracer tests. [ABSTRACT FROM AUTHOR]

• The validity of RDM method to simulate suspended sediment concentration is verified. • Integrated sediment diffusion coefficient K z ′ = β K m is proposed to study the dispersion and diffusion. • Results show that β in flow with submerged canopy is larger than that in emergent canopy flow. Based on the Lagrangian approach, this study proposes a random displacement model (RDM) to predict the concentration of suspended sediment in vegetated steady open channel flow. Validation of the method was conducted by comparing the simulated results by using the RDM with available experimental measurements for uniform open-channel flows. The method is further validated with the classical Rouse formula. To simulate the important vertical dispersion caused by vegetation in the sediment-laden open channel flow, a new integrated sediment diffusion coefficient is introduced in this study, which is equal to a coefficient β multiplying the turbulent diffusion coefficient. As such, the RDM approach for sandy flow with vegetation was established for predicting the suspended sediment concentration in low-sediment-concentration flow with both the emergent and submerged vegetation. The study shows that the value of β for submerged vegetation flow is larger than that for emergent vegetation flow. The simulated result using the RDM is in good agreement with the available experimental data, indicating that the proposed sediment diffusion coefficient model can be accurately used to investigate the sediment concentration in vegetated steady open channel flow. [ABSTRACT FROM AUTHOR]