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1.
《Advances in water resources》1996,19(4):193-206
This study deals with a method to solve the transport equations for a kinetically adsorbing solute in a porous medium with spatially varying velocity field and dispersion coefficients. Making use of the stochastic nature of a first-order kinetic process, we show that the advection-dispersion equation and the adsorption isotherm can be decoupled. Once the solution for a non-adsorbing solute is known, the method provides an exact solution for the kinetically adsorbing solute. The method is worked out in four examples. In particular we demonstrate how the method can be applied simultaneously with a numerical transport code: the advective-dispersive transport is computed numerically, whereas kinetic effects are incorporated analytically. The proposed approach may be useful in field scale applications with complex flow patterns. 相似文献
2.
Hu BX 《Ground water》2006,44(2):222-233
A Lagrangian stochastic approach is applied to develop a method of moment for solute transport in a physically and chemically nonstationary medium. Stochastic governing equations for mean solute flux and solute covariance are analytically obtained in the first-order accuracy of log conductivity and/or chemical sorption variances and solved numerically using the finite-difference method. The developed method, the numerical method of moments (NMM), is used to predict radionuclide solute transport processes in the saturated zone below the Yucca Mountain project area. The mean, variance, and upper bound of the radionuclide mass flux through a control plane 5 km downstream of the footprint of the repository are calculated. According to their chemical sorption capacities, the various radionuclear chemicals are grouped as nonreactive, weakly sorbing, and strongly sorbing chemicals. The NMM method is used to study their transport processes and influence factors. To verify the method of moments, a Monte Carlo simulation is conducted for nonreactive chemical transport. Results indicate the results from the two methods are consistent, but the NMM method is computationally more efficient than the Monte Carlo method. This study adds to the ongoing debate in the literature on the effect of heterogeneity on solute transport prediction, especially on prediction uncertainty, by showing that the standard derivation of solute flux is larger than the mean solute flux even when the hydraulic conductivity within each geological layer is mild. This study provides a method that may become an efficient calculation tool for many environmental projects. 相似文献
3.
Matheron and de Marsily [Matheron M, de Marsily G. Is the transport in porous media always diffusive? A counter-example. Water Resour Res 1980;16:901–17] studied transport in a perfectly stratified infinite medium as an idealized aquifer model. They observed superdiffusive solute spreading quantified by anomalous increase of the apparent longitudinal dispersion coefficient with the square root of time. Here, we investigate solute transport in a vertically bounded stratified random medium. Unlike for the infinite medium at asymptotically long times, disorder-induced mixing and spreading is uniquely quantified by a constant Taylor dispersion coefficient. Using a stochastic modeling approach we study the effective mixing and spreading dynamics at pre-asymptotic times in terms of effective average transport coefficients. The latter are defined on the basis of local moments, i.e., moments of the transport Green function. We investigate the impact of the position of the initial plume and the initial plume size on the (highly anomalous) pre-asymptotic effective spreading and mixing dynamics for single realizations and in average. Effectively, the system “remembers” its initial state, the effective transport coefficients show so-called memory effects, which disappear after the solute has sampled the full vertical extent of the medium. We study the impact of the intrinsic non-ergodicity of the confined medium on the validity of the stochastic modeling approach and study in this context the transition from the finite to the infinite medium. 相似文献
4.
Hakan Sirin 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,20(6):381-390
Solute plume subjected to field scale hydraulic conductivity heterogeneity shows a large dispersion/macrodispersion, which is the manifestation of existing fields scale heterogeneity on the solute plume. On the other hand, due to the scarcity of hydraulic conductivity measurements at field scale, hydraulic conductivity heterogeneity can only be defined statistically, which makes the hydraulic conductivity a random variable/function. Random hydraulic conductivity as a parameter in flow equation makes the pore flow velocity also random and the ground water solute transport equation is a stochastic differential equation now. In this study, the ensemble average of stochastic ground water solute transport equation is taken by the cumulant expansion method in order to upscale the laboratory scale transport equation to field scale by assuming pore flow velocity is a non stationary, non divergence-free and unsteady random function of space and time. Besides the stochastic explanation of macrodispersion and the velocity correction term obtained by Kavvas and Karakas (J Hydrol 179:321–351, 1996) before a new velocity correction term, which is a function of mean pore flow velocity divergence, is obtained in this study due to strict second order cumulant expansion (without omitting any term after the expansion) performed. The significance of the new velocity correction term is investigated on a one dimensional transport problem driven by a density dependent flow field. 相似文献
5.
Discrete-fracture and dual-porosity models are infrequently used to simulate solute transport through fractured unconsolidated deposits, despite their more common application in fractured rock where distinct flow regimes are hypothesized. In this study, we apply four fracture transport models--the mobile-immobile model (MIM), parallel-plate discrete-fracture model (PDFM), and stochastic and deterministic discrete-fracture models (DFMs)--to demonstrate their utility for simulating solute transport through fractured till. Model results were compared to breakthrough curves (BTCs) for the conservative tracers potassium bromide (KBr), pentafluorobenzoic acid (PFBA), and 1,4-piperazinediethanesulfonic acid (PIPES) in a large-diameter column of fractured till. Input parameters were determined from independent field and laboratory methods. Predictions of Br BTCs were not significantly different among models; however, the stochastic and deterministic DFMs were more accurate than the MIM or PDFM when predicting PFBA and PIPES BTCs. DFMs may be more applicable than the MIM for tracers with small effective diffusion coefficients (De) or for short timescales due to differences in how these models simulate diffusion or incorporate heterogeneities by their fracture networks. At large scales of investigation, the more computationally efficient MIM and PDFM may be more practical to implement than the three-dimensional DFMs, or a combination of model approaches could be employed. Regardless of the modeling approach used, fractures should be incorporated routinely into solute transport models in glaciated terrain. 相似文献
6.
A Lagrangian perturbation method is applied to develop a method of moments for solute flux through a three-dimensional nonstationary flow field. The flow nonstationarity stems from medium nonstationarity and internal and external boundaries of the study domain. The solute flux is described as a space-time process where time refers to the solute flux breakthrough through a control plane (CP) at some distance downstream of the solute source and space refers to the transverse displacement distribution at the CP. The analytically derived moment equations for solute transport in a nonstationarity flow field are too complicated to solve analytically, a numerical finite difference method is implemented to obtain the solutions. This approach combines the stochastic model with the flexibility of the numerical method to boundary and initial conditions. The developed method is applied to study the effects of heterogeneity and nonstationarity of the hydraulic conductivity and chemical sorption coefficient on solute transport. The study results indicate all these factors will significantly influence the mean and variance of solute flux. 相似文献
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8.
《Advances in water resources》2004,27(3):207-222
An Eulerian perturbation approach was applied to develop a method of moment for solute transport in a nonstationary, fractured medium. The conceptualized fractured medium is described through a dual-porosity model. Stochastic governing equations for mean concentration and concentration covariance were analytically derived to the first-order accuracy of log-conductivity variance and solved with a numerical method––a finite difference method. The developed method is called a numerical Eulerian method of moment (NEMM). This method was compared with the stationary transport theory [Water Resour. Res. 36(7) (2000) 1665] for predicting mean concentration and its spatial moments. The comparison indicated that the two methods matched very well in predicting first and second spatial moments. NEMM solutions were also compared with Monte Carlo simulations for solute transport in stationary fractured media. The results of the two methods were consistent for calculating small log conductivity variance. The theory was then used to study effects of various parameters and nonstationarity of the medium on flow and transport processes. Results indicated that medium nonstationarity would significantly influence the solute transport process. The nonstationary transport theory relaxes many assumptions adopted in stationary theories and paves the way for applying the NEMM to many environmental projects, especially in analyzing uncertainty of solute transport. 相似文献
9.
Analysis of macrodispersion through volume averaging: comparison with stochastic theory 总被引：2，自引：1，他引：1
Jie Wang Peter K. Kitanidis 《Stochastic Environmental Research and Risk Assessment (SERRA)》1999,13(1-2):66-84
Velocity variability at scales smaller than the size of a solute plume enhances the rate of spreading of the plume around
its center of mass. Macroscopically, the rate of spreading can be quantified through macrodispersion coefficients, the determination
of which has been the subject of stochastic theories. This work compares the results of a volume-averaging approach with those
of the advection dominated large-time small-perturbation theory of Dagan [1982] and Gelhar and Axness [1983]. Consider transport
of an ideal tracer in a porous medium with deterministic periodic velocity. Using the Taylor-Aris-Brenner method of moments,
it has been previously demonstrated [Kitanidis, 1992] that when the plume spreads over an area much larger than the period,
the volume-averaged concentration satisfies the advection-dispersion equation with constant coefficients that can be computed.
Here, the volume-averaging analysis is extended to the case of stationary random velocities. Additionally, a perturbation
method is applied to obtain explicit solutions for small-fluctuation cases, and the results are compared with those of the
stochastic macrodispersion theory. It is shown that the method of moments, which uses spatial averaging, for sufficiently
large volumes of averaging yields the same result as the stochastic theory, which is based on ensemble averaging. The result
is of theoretical but also practical significance because the volume-averaging approach provides a potentially efficient way
to compute macrodispersion coefficients. The method is applied to a simplified representation of the Borden aquifer.
Received: December 28, 1998 相似文献
10.
Recognizing the spatial heterogeneity of hydraulic parameters, many researchers have studied the solute transport by both groundwater and channel flow in a stochastic framework. One of the methodologies used to up‐scale the stochastic solute transport equation, from a point‐location scale to a grid scale, is the cumulant expansion method combined with the calculus for the time‐ordered exponential and the calculus for the Lie operator. When the point‐location scale transport equation is scaled up to the grid scale, using the cumulant expansion method, a new dispersion coefficient emerges in the dispersive term of the solute transport equation in addition to the molecular dispersion coefficient. This velocity driven dispersion is called ‘macrodispersion’. The macrodispersion coefficient is the integral function of the time‐ordered covariance of the random velocity field. The integral is calculated over a Lagrangian trajectory of the flow. The Lagrangian trajectory depends on the following: (i) the spatial origin of the particle; (ii) the time when the macrodispersion is calculated; and (iii) the mean velocity field along the trajectory itself. The Lagrangian trajectory is a recursive function of time because the location of the particle along the trajectory at a particular time depends on the location of the particle at the previous time. This recursive functional form of the Lagrangian trajectory makes the calculation of the macrodispersion coefficient difficult. Especially for the unsteady, spatially non‐stationary, non‐uniform flow field, the macrodispersion coefficient is a highly complex expression and, so far, calculated using numerical methods in the discrete domains. Here, an analytical method was introduced to calculate the macrodispersion coefficient in the discrete domain for the unsteady and steady, spatially non‐stationary flow cases accurately and efficiently. This study can fill the gap between the theory of the ensemble averaged solute transport model and its numerical implementations. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
11.
J. H. Cushman B. X. Hu 《Stochastic Environmental Research and Risk Assessment (SERRA)》1997,11(4):297-302
A recursive perturbation solution to the eulerian transport problem for a conservative solute in a random conductivity field
is reported. The stochastic concentration is given to arbitrary order inσ
ν, the variance of fluctuating velocity. The result gives the stochastic concentration as a perturbation to the deterministic
concentration for constant mean flow. The closed form solution is easy to implement numerically via FFT. 相似文献
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14.
A Eulerian analytical method is developed for nonreactive solute transport in heterogeneous, dual-permeability media where the hydraulic conductivities in fracture and matrix domains are both assumed to be stochastic processes. The analytical solution for the mean concentration is given explicitly in Fourier and Laplace transforms. Instead of using the fast fourier transform method to numerically invert the solution to real space (Hu et al., 2002), we apply the general relationship between spatial moments and concentration (Naff, 1990; Hu et al., 1997) to obtain the analytical solutions for the spatial moments up to the second for a pulse input of the solute. Owing to its accuracy and efficiency, the analytical method can be used to check the semi-analytical and Monte Carlo numerical methods before they are applied to more complicated studies. The analytical method can be also used during screening studies to identify the most significant transport parameters for further analysis. In this study, the analytical results have been compared with those obtained from the semi-analytical method (Hu et al., 2002) and the comparison shows that the semi-analytical method is robust. It is clearly shown from the analytical solution that the three factors, local dispersion, conductivity variation in each domain and velocity convection flow difference in the two domains, play different roles on the solute plume spreading in longitudinal and transverse directions. The calculation results also indicate that when the log-conductivity variance in matrix is 10 times less than its counterpart in fractures, it will hardly influence the solute transport, whether the conductivity field is matrix is treated as a homogeneous or random field. 相似文献
15.
We analyze the impact of conditioning to measurements of hydraulic transmissivity on the transport of a conservative solute. The effects of conditioning on solute transport are widely discussed in the literature, but most of the published works focuses on the reduction of the uncertainty in the prediction of the plume dispersion. In this study both ensemble and effective plume moments are considered for an instantaneous release of a solute through a linear source normal to the mean flow direction, by taking into account different sizes of the source. The analysis, involving a steady and spatially inhomogeneous velocity field, is developed by using the stochastic finite element method. Results show that conditioning reduces the ensemble moment in comparison with the unconditioned case, whereas the effective dispersion may increase because of the contribution of the spatial moments related to the lack of stationarity in the flow field. As the number of conditioning points increases, this effect increases and it is significant in both the longitudinal and transverse directions. Furthermore, we conclude that the moment derived from data collected in the field can be assessed by the conditioned second-order spatial moment only with a dense grid of measured data, and it is manifest for larger initial lengths of the plume. Nevertheless, it seems very likely that the actual dispersion of the plume may be underestimated in practical applications. 相似文献
16.
Probabilistic analysis by Monte Carlo Simulation method (MCSM) is a computationally prohibitive task for a reactive solute transport involving coupled PDEs with nonlinear source/sink terms in 3-D heterogeneous porous media. The perturbation based stochastic finite element method (SFEM) is an attractive alternative method to MCSM as it is computationally efficient and accurate. In the present study SFEM is developed for solving nonlinear reactive solute transport problem in a 3-D heterogeneous medium. Here the solution of the biodegradation problem involving a single solute by a single class of microorganisms coupled with dynamic microbial growth is attempted using this method. The SFEM here produces a second-order accurate solution for the mean and a first-order accurate solution for the standard deviation of concentrations. In this study both the physical parameters (hydraulic conductivity, porosity, dispersivity and diffusion coefficient) and the biological parameters (maximum substrate utilization rate and the coefficient of cell decay) are considered as spatially varying random fields. A comparison between the MCSM and SFEM for the mean and standard deviation of concentration is made for 1-D and 3-D problem. The effects of heterogeneity on the degradation of substrate and growth of biomass concentrations for a range of variances of input parameters are discussed for both 1-D and 3-D problems. 相似文献
17.
Quantifying hyporheic solute dynamics has been limited by our ability to assess the magnitude and extent of stream interactions with multiple domains: mobile subsurface storage (MSS, e.g., freely flowing pore water) and immobile subsurface storage (ISS, e.g., poorly connected pore water). Stream-tracer experiments coupled with solute transport modeling are frequently used to characterize lumped MSS and ISS dynamics, but are limited by the ability to sample only “mobile” water and by window of detection issues. Here, we couple simulations of near-surface electrical resistivity (ER) methods with conservative solute transport to directly compare solute transport with ER interpretations, and to determine the ability of ER to predict spatial and temporal trends of solute distribution and transport in stream–hyporheic systems. Results show that temporal moments from both ER and solute transport data are well correlated for locations where advection is not the dominant solute transport process. Mean arrival time and variance are especially well-predicted by ER interpretation, providing the potential to estimate rate-limited mass transport (i.e. diffusive) parameters from these data in a distributed domain, substantially increasing our knowledge of the fate and transport of subsurface solutes. 相似文献
18.
Chunlin Huang Bill X. Hu Xin Li Ming Ye 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(8):1155-1167
Hydraulic conductivity distribution and plume initial source condition are two important factors affecting solute transport
in heterogeneous media. Since hydraulic conductivity can only be measured at limited locations in a field, its spatial distribution
in a complex heterogeneous medium is generally uncertain. In many groundwater contamination sites, transport initial conditions
are generally unknown, as plume distributions are available only after the contaminations occurred. In this study, a data
assimilation method is developed for calibrating a hydraulic conductivity field and improving solute transport prediction
with unknown initial solute source condition. Ensemble Kalman filter (EnKF) is used to update the model parameter (i.e., hydraulic
conductivity) and state variables (hydraulic head and solute concentration), when data are available. Two-dimensional numerical
experiments are designed to assess the performance of the EnKF method on data assimilation for solute transport prediction.
The study results indicate that the EnKF method can significantly improve the estimation of the hydraulic conductivity distribution
and solute transport prediction by assimilating hydraulic head measurements with a known solute initial condition. When solute
source is unknown, solute prediction by assimilating continuous measurements of solute concentration at a few points in the
plume well captures the plume evolution downstream of the measurement points. 相似文献
19.
《Advances in water resources》2004,27(4):445-464
The upscaling of dispersivity in solute transport in heterogeneous aquifers is addressed with a numerical stochastic formulation. This work represents progress toward converting theory into scalable numerical models that can be compared to laboratory experiments. Traditional global assumptions of low variance, ergodicity, single correlation scale, stationarity, and the like are avoided through the use of a flexible Lagrangian numerical, not analytical, framework, which allows assumptions to be local. A method of calculating grid-block upscaled dispersivities is presented. Computational results are obtained for a heterogeneous tank experiment, with reasonable behavior. 相似文献
20.
Can a Time Fractional‐Derivative Model Capture Scale‐Dependent Dispersion in Saturated Soils? 
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下载免费PDF全文 Rhiannon M. Garrard Yong Zhang Song Wei HongGuang Sun Jiazhong Qian 《Ground water》2017,55(6):857-870
Time nonlocal transport models such as the time fractional advection‐dispersion equation (t‐fADE) were proposed to capture well‐documented non‐Fickian dynamics for conservative solutes transport in heterogeneous media, with the underlying assumption that the time nonlocality (which means that the current concentration change is affected by previous concentration load) embedded in the physical models can release the effective dispersion coefficient from scale dependency. This assumption, however, has never been systematically examined using real data. This study fills this historical knowledge gap by capturing non‐Fickian transport (likely due to solute retention) documented in the literature (Huang et al. 1995) and observed in our laboratory from small to intermediate spatial scale using the promising, tempered t‐fADE model. Fitting exercises show that the effective dispersion coefficient in the t‐fADE, although differing subtly from the dispersion coefficient in the standard advection‐dispersion equation, increases nonlinearly with the travel distance (varying from 0.5 to 12 m) for both heterogeneous and macroscopically homogeneous sand columns. Further analysis reveals that, while solute retention in relatively immobile zones can be efficiently captured by the time nonlocal parameters in the t‐fADE, the motion‐independent solute movement in the mobile zone is affected by the spatial evolution of local velocities in the host medium, resulting in a scale‐dependent dispersion coefficient. The same result may be found for the other standard time nonlocal transport models that separate solute retention and jumps (i.e., displacement). Therefore, the t‐fADE with a constant dispersion coefficient cannot capture scale‐dependent dispersion in saturated porous media, challenging the application for stochastic hydrogeology methods in quantifying real‐world, preasymptotic transport. Hence improvements on time nonlocal models using, for example, the novel subordination approach are necessary to incorporate the spatial evolution of local velocities without adding cumbersome parameters. 相似文献