ArticleScientific reports2026
Quantifying solute back-diffusion in heterogeneous dual-permeability systems: effects of flow velocity and matrix hydraulic conductivity using electrical resistivity monitoring.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Groundwater contamination in heterogeneous aquifer systems containing high-permeability zones (analogous to fractures) and adjacent low-permeability zones (analogous to rock matrices) persists long after source removal due to back-diffusion, whereby contaminants stored in low-permeability zones gradually migrate back into high-permeability pathways. While this process critically controls contamination longevity and remediation effectiveness, the coupled influence of groundwater flow velocity and matrix hydraulic conductivity on back-diffusion remains poorly quantified. We conducted systematic laboratory experiments using sandbox models to simulate heterogeneous dual-permeability systems across four hydraulic conductivity levels and four flow velocities. Real-time electrical resistivity monitoring tracked sodium chloride tracer movement, enabling continuous, minimally-invasive characterization of back-diffusion dynamics. Results demonstrate strong inverse relationships between flow velocity and back-diffusion intensity: a 30% flow increase reduced contaminant release by 78% in high-conductivity systems. Matrix hydraulic conductivity exerted equally significant control, with high-conductivity materials accelerating contaminant exchange (reducing delay times by 65% and back-diffusion duration by 40%), while low-conductivity materials sustained release for over 4000 s. Dimensionless analysis using Péclet and Damköhler numbers demonstrated that all 16 experimental datasets collapse onto a single relationship, confirming the generalizability of the findings.These findings establish quantitative relationships between hydraulic properties and back-diffusion behavior, providing a predictive framework for assessing long-term contamination persistence and optimizing remediation strategies in heterogeneous aquifer systems.
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