Natural attenuation and in situ oxidation are commonly considered as low-cost alternatives to ex situ remediation. The efficiency of such remediation techniques is hindered by difficulties in obtaining good dilution and mixing of the contaminant, in particular if the plume deformation is physically constrained by an array of wells, which serves as a containment system. In that case, dilution may be enhanced by inducing an engineered sequence of injections and extractions from such pumping system, which also works as a hydraulic barrier. This way, the aquifer acts as a natural mixer, in a manner similar to the industrialized engineered mixers. Improving the efficiency of hydrogeological mixers is a challenging task, owing to the need to use a 3D setup while relieving the computational burden. Analytical solutions, though approximated, are a suitable and efficient tool to seek the optimum solution among all possible flow configurations. Here we develop a novel physically-based model to demonstrate how the combined spatiotemporal fluctuations of the water fluxes control solute trajectories and residence time distributions and therefore, the effectiveness of contaminant plume dilution and mixing. Our results show how external forcing configurations are capable of inducing distinct time-varying groundwater flow patterns which will yield different solute dilution rates.

This paper employs stochastic analysis to investigate the combined effect of temporal and spatial variability on the temporal variance of baseflow in large catchments. The study makes use of the well‐known aggregated reservoir model, representing the catchment as a network of parallel linear reservoirs. Each reservoir models a sub‐catchment as an independent unit whose discharge temporal variation is characterized by a response time. By treating the rainfall‐generated recharge and the sub‐catchment response times as random variables, the statistical temporal moments of total baseflow are quantified. Comparisons are made between the temporal variance of baseflow in the aggregated reservoir model and that of a single homogeneous reservoir to define an upscaled response time. The analysis of the statistical moments of the random baseflow reveals that the number of reservoirs N has a weak impact on baseflow variance, with ergodic conditions achieved even with a small number of reservoirs. The study highlights that the ratio between the recharge correlation time and the geometric mean of the sub‐catchment response times plays a critical role in baseflow damping and the upscaled response. The results indicate that the dynamics of baseflow generation depend not only on the catchment hydro‐geological structure but also on the variability of the input signal. This research underscores the importance of understanding the combined influences of hydro‐geological factors and recharge input variability for baseflow prediction under uncertainty. The present study should be regarded as a first step, setting the theoretical framework for future research toward incorporating field data.