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Mathematical models of the transport and fate of dissolved chemicals in groundwater are becoming increasingly important tools in understanding, managing, and remediating groundwater contamination. The success of such models is dependent on: 1) how well the relevant physical, chemical, and microbiological processes controlling subsurface transport are represented with mathematical equations, and 2) how accurately and efficiently the equations are solved with numerical methods that discretize the equations over space and time. The computational burden associated with multidimensional, multicomponent, numerical solute transport models can be prohibitive. In this project, we have implemented and extended a local adaptive grid refinement (LAGR) method of Berger and Oliger (1984) to solve CPU-intensive transport problems efficiently and accurately. The method tracks error-prone regions of the solution domain and supplies high-resolution subgrids where they are locally needed while maintaining relatively few nodes elsewhere on a coarse base grid. Novel features include a unique method for detecting a priori where the numerical error is unacceptable, variable time step control which allows smaller time steps on subgrids than on the base grid, and a modular framework which allows easy exchange of partial differential equation solvers to accommodate different problem formulations.We use simulations for uniform and nonuniform flow fields and for single, nonreactive species and multiple, reactive species to demonstrate and evaluate the LAGR method. The cost and accuracy of LAGR simulations depends on design parameters controlling where subgrids are created, how frequently they are created, and how large they are once they are created. For any particular problem there is a trade-off between cost and accuracy, depending on how the design parameters are chosen. Although the optimal set of design parameters is nonunique, we have been able to provide important insight into the choice of parameters for a desired solution accuracy. Using this insight, solutions with accuracies comparable to those achieved with a uniform fine grid are obtained at between 15 and 30% of the computational cost.

Modeling of hydrologic processes using multiphysics modeling packages shows significant promise in a number of applications. However, these packages have not yet developed a complete set of implementations for boundary conditions important in hydrologic modeling. Three such boundary conditions—rainfall infiltration, seepage faces, and evapotranspiration fluxes—are implemented using the generic boundary condition and internal sink routines provided in one multiphysics package, COMSOL multiphysics. Comparison with results from previous simulations using dedicated hydrologic models demonstrates that with care and creativity these boundary conditions can be implemented accurately and efficiently. Boundary condition implementation should not limit the applicability of multiphysics models to a broad set of problems of interest to the hydrologic community. [ABSTRACT FROM AUTHOR]

The three-dimensional movement of a tracer plume containing bromide and chloride is investigated using the data base from a large-scale natural gradient field experiment on groundwater solute transport. The analysis focuses on the zeroth-, first-, and second-order spatial moments of the concentration distribution. These moments define integrated measures of the dissolved mass, mean solute velocity, and dispersion of the plume. Moments are estimated from the point observations using quadrature approximations tailored to the density of the sampling network. The estimators appear to be robust, with acceptable sampling variability. Estimates of the mass in solution for both bromide and chloride demonstrate that the tracers behaved conservatively, as expected. Analysis of the first-order moment estimates indicates that the experimental tracer plumes traveled along identical trajectories. The horizontal trajectory is linear and aligned with the hydraulic gradient. The vertical trajectory is curvilinear, concave upward. The total vertical displacement is small, however, so that the vertical component of the mean solute velocity vector is negligible. The estimated mean solute velocity is identical for both tracers (0.091 m/day) and is spatially and temporally uniform for the first 647 days of travel time. After 647 days of transport, the plume apparently encountered a relatively large-scale heterogeneity in the velocity field, leading to a distinct vertical layering, and slowing the rate of advance of the center of mass of the plume as a whole. The estimated horizontal components of the covariance tensor evolve over time in a manner consistent with the qualitative shape changes observed from plots of the concentration data. The major principal axis, initially aligned roughly perpendicular to the hydraulic gradient, rotates smoothly over time until it is nearly aligned with the mean solute velocity vector, as the plume itself elongates and orients its long axis with the direction of movement. Plots of the components of the covariance tensor as functions of time show evidence of what is commonly called 'scale-dependent' dispersion: the rate of growth of the covariance over time is not linear. The theoretical results of G. Dagan (1984) calibrate well to the estimated covariance data for the first 647 days of transport. The calibrated values of the parameters of the hydrualic conductivity distribution closely match independently measured values from the site. The asymptotic longitudinal dispersivity obtained from the calibration is 0.49 m, although asymptotic conditions were apparently not reached. The estimated covariance terms for the last sampling session, 1038 days after injection, are inconsistent with the earlier data and with the Dagan model, particularly for the transverse and off-diagonal components. This behavior is probably attributable to the observed large-scale heterogeneity in the velocity field. [ABSTRACT FROM AUTHOR]