An Extended Colloid Filtration Theory for Modeling Escherichia coli Transport in 3-D Fracture Networks

Microbial transport in fractured carbonate rock using enhanced solutions is a significant and neglected research topic in the literature. We propose an extended colloid filtration theory (CFT) combined with a particle-tracking following streamlines (PTFS) model for the rapid prediction of breakthrough curves (BTCs) and plumes of pathogens in three-dimensional (3-D) discrete fracture networks (DFNs). We adapted CFT in porous media to pathogen transport in fractures containing Terra Rossa (soil) deposits. As an example of the model capability, a simulation was used to predict the 3-D motion field and Escherichia coli count in groundwater originating from the Forcatella managed aquifer recharge (MAR) Facility (Brindisi, Italy) using a DFN composed of 3,900 fractures. In arid regions, MAR facilities are significant for sustaining basic human needs, such as freshwater supply for drinking and crop production. The Markov chain Monte Carlo (MCMC) technique was applied to E. coli counts in the collected water samples to increase data representativeness. The pathogen transport coefficients were further supported by batch filtration tests carried out in the CNR/IRSA Laboratory (Bari, Italy). The mean E. coli attachment rate coefficient of 0.15 × 10-8 m2 d-1 (sticking efficiency = 1.1 × 10-8 m) resulted in a 2.1 log10 removal in 600 m of reclaimed water filtration. The simulation output visualized the E. coli 3-D pathways in groundwater and the positions of contaminated groundwater spring outflows on Forcatella Beach. The simulation results agreed with the mean MCMC output of E. coli concentrations in bathing water under unperturbed geochemical and environmental flow and transport conditions. However, results indicate that concentrations of pathogenic strains, parasites, and enteric viruses may enter the marine environment of MAR sites during flood periods.