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This paper presents an analytical study of organic contaminants transport in a cut-off wall and aquifer dual-domain system, considering the effects of the inlet boundary conditions and cut-off structural arrangements. The comprehensive sensitivity analysis of parameters focusing on the breakthrough time, attenuation time and cumulative concentration are presented using the Monte Carlo simulation and Sobol global method. The simplified constant inlet boundary condition can lead to an excessively conservative prediction of the contaminant breakthrough compared to the 'finite mass' and 'decaying source' boundary conditions. The cut-off wall hydraulic performance can be enhanced by reducing the contaminant's head loss, shape factor, half-life and cut-off wall hydraulic conductivity while increasing the retardation factor. The contaminant's half-life can largely influence the maximum contaminant concentration, attenuation time and breakthrough time. For example, the maximum contaminant concentrations for T 1/2 = 1.4 years and T 1/2 = 100 years are 13 and 123 times greater than that for T 1/2 = 0.1 year, respectively. The influence of the variation of shape factor on the breakthrough curve should be taken into consideration. Altering the structural arrangement of the cut-off wall to accommodate a smaller shape factor increases the contaminant breakthrough time. The proposed solution allows the analysis of a cut-off wall and aquifer system with different inlet boundary conditions and structural arrangements of the cut-off wall. • An analytical model of organic contaminants transport in a CAS is proposed. • Monte Carlo simulation and Sobol global method are used for sensitivity analysis. • Different inlet boundary conditions and structural arrangements are investigated. • A constant contaminant concentration leads to conservative predictions. • Altering the structural arrangement can enhance the performance of the barrier. [ABSTRACT FROM AUTHOR]

Estimating spatial distributions of the hydraulic conductivity in heterogeneous aquifers has always been an important and challenging task in hydrology. Generally, the hydraulic conductivity field is determined from hydraulic head or pressure measurements. In the present study, we propose to use temperature data as source of information for characterizing the spatial distributions of the hydraulic conductivity field. In this way, we performed a laboratory sandbox experiment with the aim of imaging the heterogeneities of the hydraulic conductivity field from thermal monitoring. During the laboratory experiment, we injected a hot water pulse, which induces a heat plume motion into the sandbox. The induced plume was followed by a set of thermocouples placed in the sandbox. After the temperature data acquisition, we performed a hydraulic tomography using the stochastic Hybrid Monte Carlo approach, also called the Hamiltonian Monte Carlo (HMC) algorithm to invert the temperature data. This algorithm is based on a combination of the Metropolis Monte Carlo method and the Hamiltonian dynamics approach. The parameterization of the inverse problem was done with the Karhunen-Loève (KL) expansion to reduce the dimensionality of the unknown parameters. Our approach has provided successful reconstruction of the hydraulic conductivity field with low computational effort. [ABSTRACT FROM AUTHOR]

• Heterogeneous aquifers are modeled with log-normal random conductivity fields. • Numerical schemes are tested on two-dimensional benchmark flow problems. • Code verification performed by comparison with analytical manufactured solutions. • Validation done through comparisons between MC statistics and first-order results. • Limited computational feasibility for exponentially correlated log-conductivity. This article presents numerical investigations on accuracy and convergence properties of several numerical approaches for simulating steady state flows in heterogeneous aquifers. Finite difference, finite element, discontinuous Galerkin, spectral, and random walk methods are tested on two-dimensional benchmark flow problems. Realizations of log-normal hydraulic conductivity fields are generated by Kraichnan algorithms in closed form as finite sums of random periodic modes, which allow direct code verification by comparisons with manufactured reference solutions. The quality of the methods is assessed for increasing number of random modes and for increasing variance of the log-hydraulic conductivity fields with Gaussian and exponential correlation. Experimental orders of convergence are calculated from successive refinements of the grid. The numerical methods are further validated by comparisons between statistical inferences obtained from Monte Carlo ensembles of numerical solutions and theoretical first-order perturbation results. It is found that while for Gaussian correlation of the log-conductivity field all the methods perform well, in the exponential case their accuracy deteriorates and, for large variance and number of modes, the benchmark problems are practically not solvable with reasonably large computing resources, for all the methods considered in this study. [ABSTRACT FROM AUTHOR]

• Super-diffusion is affected differently by the thickness and width of hydrofacies. • Bi-peak super-diffusion is affected by the geometry of initial source at early time. • Bi-peak super-diffusion can be captured by multi-domain fractional-derivative model. Dissolved-phase contaminants experiencing enhanced diffusion (i.e., "super-diffusion") with a pronounced leading plume edge can pose risk for groundwater quality. The drivers for complex super-diffusion in geological media, however, are not fully understood. This study investigates the impacts of hydrofacies' mean lengths and the initial source geometry, motivated by a hydrofacies model built recently for the well-known MADE aquifer, on the spatial pattern of super-diffusion for two-dimensional alluvial aquifer systems. Monte Carlo simulations show that the bimodal velocity distribution, whose pattern is affected by the hydrofacies' mean lengths, leads to super-diffusion of solutes with a bi-peak plume snapshot in alluvial settings where advection dominates transport. A larger longitudinal mean length (i.e., width) for hydrofacies with high hydraulic conductivity (K) enhances the connectivity of preferential pathways, resulting in higher values in the bimodal velocity distribution and an enhanced leading front for the bi-peak plume snapshot, while the opposite impact is identified for the hydrofacies' vertical mean length (i.e., thickness) on the bi-peak super-diffusion. A multi-domain non-local transport model is then proposed, extending upon the concept of the distributed-order fractional derivative, to quantify the evolution of bi-peak super-diffusion due to differential advection and mobile-mobile mass exchange for solute particles moving in hydrofacies with distinct K. Results show that the bi-peak super-diffusion identified for the MADE site and perhaps the other similar aquifers, which is affected by the initial source geometry at an early stage and the thickness and width of high- K hydrofacies during all stages, can be quantified by the mobile-mobile fractional-derivative model. Porous medium dimensionality and stochastic model comparison are also discussed to further explore the nature of bi-peak super-diffusion in alluvial systems. [ABSTRACT FROM AUTHOR]