Importance of reversible attachment in predicting E. coli transport in saturated aquifers from column experiments

• E. coli transport below freshly-excavated pond receiving latrine effluent modeled.
• Anisotropy in hydraulic conductivity greatly limited E. coli depth penetration.
• Reversible and irreversible attachment of E. coli required to match field data.
• Laboratory-predicted E. coli transport matches field data within factor of two.
• Kinetic interaction parameters relatively insensitive to scale of measurement.

Drinking water wells indiscriminatingly placed adjacent to fecal contaminated surface water represents a significant but difficult to quantify health risk. Here we seek to understand mechanisms that limit the contamination extent by scaling up bacterial transport results from the laboratory to the field in a well constrained setting. Three pulses of Escherichia coli originating during the early monsoon from a freshly excavated pond receiving latrine effluent in Bangladesh were monitored in 6 wells and modeled with a two-dimensional (2-D) flow and transport model conditioned with measured hydraulic heads. The modeling was performed assuming three different modes of interaction of E. coli with aquifer sands: (1) irreversible attachment only (best-fit ki = 7.6 day−1); (2) reversible attachment only (ka = 10.5 and kd = 0.2 day−1); and (3) a combination of reversible and irreversible modes of attachment (ka = 60, kd = 7.6, ki = 5.2 day−1). Only the third approach adequately reproduced the observed temporal and spatial distribution of E. coli, including a 4-log10 lateral removal distance of ∼9 m. In saturated column experiments, carried out using aquifer sand from the field site, a combination of reversible and irreversible attachment was also required to reproduce the observed breakthrough curves and E. coli retention profiles within the laboratory columns. Applying the laboratory-measured kinetic parameters to the 2-D calibrated flow model of the field site underestimates the observed 4-log10 lateral removal distance by less than a factor of two. This is promising for predicting field scale transport from laboratory experiments.