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Dispersion Transport Equation with Distance-Dependent Coefficients

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Dispersion Transport Equation with Distance-Dependent Coefficients Journal of Hydrology 390 (2010) 57–65 Contents lists available at ScienceDirect Journal of Hydrology journal homepage: www.elsevier.com/locate/jhydrol Analytical solution for one-dimensional advection–dispersion transport equation with distance-dependent coefficients J.S. Pérez Guerrero a, T.H. Skaggs b,* a Radioactive Waste Division, Brazilian Nuclear Energy Commission, DIREJ/DRS/CNEN, R. General Severiano 90, 22290-901 RJ-Rio de Janeiro, Brazil b US Salinity Laboratory, USDA-ARS, Riverside, CA, USA article info summary Article history: Mathematical models describing contaminant transport in heterogeneous porous media are often formu- Received 15 April 2010 lated as an advection–dispersion transport equation with distance-dependent transport coefficients. In Received in revised form 16 June 2010 this work, a general analytical solution is presented for the linear, one-dimensional advection–dispersion Accepted 18 June 2010 equation with distance-dependent coefficients. An integrating factor is employed to obtain a transport equation that has a self-adjoint differential operator, and a solution is found using the generalized inte- This manuscript was handled by Geoff Syme, Editor-in-Chief gral transform technique (GITT). It is demonstrated that an analytical expression for the integrating factor exists for several transport equation formulations of practical importance in groundwater transport mod- eling. Unlike nearly all solutions available in the literature, the current solution is developed for a finite Keywords: Contaminant transport spatial domain. As an illustration, solutions for the particular case of a linearly increasing dispersivity are Heterogeneous porous media developed in detail and results are compared with solutions from the literature. Among other applica- Distance-dependent dispersion tions, the current analytical solution will be particularly useful for testing or benchmarking numerical Analytical solution transport codes because of the incorporation of a finite spatial domain. Integral transform Published by Elsevier B.V. Integrating factor 1. Introduction or distance-dependent coefficients (Yates, 1990; Chrysikopoulos et al., 1990; Yates, 1992; Huang et al., 1996; Logan, 1996; Zop- The literature contains many analytical solutions for solute pou and Knight, 1997; Hunt, 1998, 1999, 2002; Pang and Hunt, transport in homogeneous porous media. These solutions, which 2001; Al-Humoud and Chamkha, 2007; Liu and Si, 2008; Chen, have been collected in various compendiums (Codell et al., 1982; 2007; Chen et al., 2003, 2007, 2008a,b; Kumar et al., 2010). van Genuchten, 1982; Javandel et al., 1984; Wexler, 1992), were While most of these solutions are applicable to a range of prob- found by solving the linear advection–dispersion transport equa- lems involving (effectively) semi-infinite or infinite media, other tion with constant coefficients, subject to appropriate boundary applications require consideration of finite media, such as anal- and initial conditions. Solutions are available for one-, two-, and ysis of transport in lysimeters or columns, or benchmarking three-dimensional spatial domains, with the vast majority being numerical transport codes. In these types of problems, the effect applicable to semi-infinite or infinite media. However, the advec- of the exit boundary may not be negligible. tion–dispersion equation with constant coefficients may not be One reason for the lack of progress in developing solutions for appropriate for transport in heterogeneous media, where transport finite domains is that the solution procedures tend to be relatively coefficients can be variable in space and/or time. Relatively few complicated, requiring difficult or tedious mathematical deriva- analytical results are available for the case of non-constant coeffi- tions and manipulations. However, the advent of software such cients, especially for the case of finite media. as Mathematica (Wolfram Research, Inc., 2007) with capabilities Analytical solutions for heterogeneous porous media include for symbolic manipulation has made these solution procedures solutions obtained for transport equations with time-dependent more tractable. coefficients (Barry and Sposito, 1989; Basha and El-Habel, 1993; Also facilitating the development of new solutions are system- Aral and Liao, 1996; Marinoschi et al., 1999; Kumar et al., 2010) atized integral transform techniques (ITTs) (Mikhailov and Ozisik, 1984). As noted by Ozisik (1993), the classic ITT (CITT) provides a systematic, efficient, and straightforward approach for the analyt- ical solution of both transient and steady problems, with both * Corresponding author. Address: US Salinity Laboratory, 450 W. Big Springs Rd., Riverside, CA 92507, USA. Tel.: +1 951 369 4853; fax: +1 951 342 4964. homogeneous and non-homogeneous boundary conditions. A large E-mail address: [email protected] (T.H. Skaggs). variety of heat and mass diffusion problems have been categorized 0022-1694/$ - see front matter Published by Elsevier B.V. doi:10.1016/j.jhydrol.2010.06.030 58 J.S. Pérez Guerrero, T.H. Skaggs / Journal of Hydrology 390 (2010) 57–65 Nomenclature a slope of dispersivity–distance relationship t, T dimensionless and dimensional time A ðnÞ; A ðnÞ 00 01 coefficients in generic transport equation U mean transport velocity A10ðnÞ; A20ðnÞ x, X dimensionless and dimensional space coordinate B mathematical operator specifying boundary conditions k Yr Bessel function of the second kind and order r c, C dimensionless and dimensional solute concentration w(n) coefficient in self-adjoint equation cI(x), CI dimensionless and dimensional initial solute concentra- tion Greek symbols C0 boundary (first-type) or influent (third-type) concentra- a; a dimensionless and dimensional dispersivity tion bi eigenvalue c steady state solute concentration (dimensionless) 1 dij Kronecker delta D; D dimensionless and dimensional dispersion coefficient gk coefficient in boundary condition dM,DM dimensionless and dimensional coefficient of molecular h unknown function with homogeneous boundary condi- diffusion tions f integral transformed initial condition i hi integral transform of the function h g(nk) source term in generic boundary condition k decay constant Hk coefficient in boundary condition l ratio of generic transport coefficients, A00(n)/A01(n) Ir modified Bessel function of first kind and order r n space variable in generic transport equation J Bessel function of first kind and order r r n0, n1 position of boundaries in generic transport equation Kr modified Bessel function of second kind and order r p 3.14... k index denoting position r equal to 1/a L advection–dispersion operator s time variable in generic transport equation L0 domain length u(x) auxiliary function Ni norm of ith eigenfunction wi eigenfunction p(n) integrating factor ~ wi normalized eigenfucntion q(n) coefficient in operator S x(n, s) dependent variable in generic transport equation Q(n) source-sink term in the generic transport equation x1(n) steady state (s ? 1)ofx(n, s) R retardation coefficient xI(n) initial condition of x(n, s) S self-adjoint operator and treated systematically using this technique, creating a unified 2. General problem formulation approach for solving those problems (Mikhailov and Ozisik, 1984). Transport equations not immediately analytically solvable with the Consider a one-dimensional finite medium with space variable CITT can often be transformed into an amenable form using tech- n and time variable s. For some quantity x x(n, s), a generic niques such as algebraic substitution or integrating factor methods advection–dispersion transport equation with distance-dependent (e.g. Pérez Guerrero et al., 2009a,b, 2010). transport coefficients can be formulated as: Cotta (1993) extended the CITT to develop the generalized inte- gral transform technique (GITT). The GITT permits the analytical or @x @ @x @x A01ðnÞ ¼ DðnÞ À UðnÞ À A00ðnÞx þ QðnÞ; semi-analytical solution of more general parabolic or elliptic prob- @s @n @n @n lems, both linear and nonlinear. In the GITT, the unknown function n0 < n < n1 ð1Þ is represented in terms of an eigenfunction series expansion. The solution is obtained in the following steps (Cotta, 1993): where n0 and n1 are the locations of the boundaries, A01(n), D(n), U(n), and A00(n) are distance-dependent coefficients, and Q(n)isa (a) Choose an appropriate auxiliary eigenvalue problem and source-sink term. On the right side of Eq. (1), the first term is the find the associated eigenvalues, eigenfunctions, norm, and dispersion term, the second is the advection term, and the third orthogonalization property. term represents processes such as the first-order decay or produc- (b) Develop the integral and inverse transforms. tion. Eq. (1) is a generic transport equation which may be either (c) Transform the partial differential equation into a system of dimensional or dimensionless. ordinary differential or algebraic equations. Expanding the dispersion term and grouping like terms gives, (d) Solve the ordinary differential or algebraic system. 2 (e) Use the inverse transform to obtain the unknown @x @ x @x A01ðnÞ ¼ A20ðnÞ þ A10ðnÞ À A00ðnÞx þ QðnÞ; function. @s @n2 @n n0 < n < n1 ð2aÞ The aim of the present study is to develop an analytical solution for solute transport in finite, heterogeneous porous media. For this where purpose, a general advection–dispersion transport equation with @DðnÞ distance-dependent coefficients is transformed through the use A ðnÞ¼DðnÞ; A ðnÞ¼ À UðnÞð2b; cÞ 20 10 @n of an integrating factor and a
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