The need to quantify and/or reduce uncertainty associated with transport model predictions as well as the ongoing research on solute transport upscaling require a numerical method for simulating transport which is highly computational efficient even for models with millions of grid cells and which is not prone to numerical errors. One valuable alternative tool for this purpose is the random walk particle tracking method. This thesis attempts to examine its fundamental concepts, extend its capacities, and illustrate its applicability to field problems.
The first paper reviews and assesses the basic mathematical concepts of the random walk methodology as well as its limitations and advantages. Different numerical implementation methods to overcome the problem of local solute mass conservation are examined using a simple two-layer case as well as synthetic heterogeneous two dimensional conductivity fields. It is demonstrated that the interpolation method using a hybrid scheme, i.e., linear interpolation for velocities and tri/bi-linear interpolation for the dispersion tensor field, provides a local as well as global divergence-free velocity field and that it furthermore approximates well mass balance at grid interfaces of adjacent cells with contrasting hydraulic conductivities.
The second paper presents a new approach to include multirate mass transfer processes into random walk particle tracking. Performing a Bernoulli trial on the appropriate phase transition probabilities, derived using the normalized zeroth spatial moments of the multirate transport equations, the particle distribution between the mobile domain and any immobile domain can be determined. Examples for the first-order mass transfer and the multirate mass transfer are illustrated and compared satisfactorily with analytical and semi-analytical solutions. Various implementation criteria are investigated to assure a proper simulation of the mass transfer processes.
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