Wael El-Dakhakhni

The efficient management and remediation of contaminated fractured aquifers necessitate an accurate prediction of the spatial distribution of contaminant concentration within the system. Related existing analytical solutions are only applicable to single fractures and have not yet been extrapolated to the aquifer scale where a network of connected fractures exists. The Random Walk Particle Tracking (RWPT) method has been extensively adopted for concentration mapping in Discrete Fracture Networks (DFNs), albeit at exorbitant computational costs and without efficiently accommodating complex physical processes (e.g., two-site kinetics). This study introduces an analytically enhanced Spatiotemporal Random Walk (STRW) approach that facilitates the efficient time-dependent mapping of contaminant concentration in DFNs. The STRW approach employs a distribution function to simultaneously estimate the displacement of particles released through the system either instantaneously or over time. The STRW approach efficiently reproduced the contaminant concentration, calculated using available analytical solutions under a range of fate and transport mechanisms. The efficacy of the STRW approach is also confirmed in a synthetic impermeable DFN through replicating the concentration maps produced using the RWPT method. The developed approach represents an accurate and computationally efficient dynamic concentration mapping technique that can support the effective operation, management, and remediation of fractured aquifers under contamination events.