Probabilistic multi-scale modeling of pathogen dynamics in rivers

Monday, 15 December 2014
Aaron Ian Packman, Northwestern University, Evanston, IL, United States, Jennifer D Drummond, Northwestern Univeristy, Evanston, IL, United States and Antoine F Aubeneau, University of Notre Dame, Notre Dame, IN, United States
Most parameterizations of microbial dynamics and pathogen transport in surface waters rely on classic assumptions of advection-diffusion behavior in the water column and limited interactions between the water column and sediments. However, recent studies have shown that strong surface-subsurface interactions produce a wide range of transport timescales in rivers, and greatly the opportunity for long-term retention of pathogens in sediment beds and benthic biofilms. We present a stochastic model for pathogen dynamics, based on continuous-time random walk theory, that properly accounts for such diverse transport timescales, along with the remobilization and inactivation of pathogens in storage reservoirs. By representing pathogen dynamics probabilistically, the model framework enables diverse local-scale processes to be incorporated in system-scale models. We illustrate the application of the model to microbial dynamics in rivers based on the results of a tracer injection experiment. In-stream transport and surface-subsurface interactions are parameterized based on observations of conservative tracer transport, while E. coli retention and inactivation in sediments is parameterized based on direct local-scale experiments. The results indicate that sediments are an important reservoir of enteric organisms in rivers, and slow remobilization from sediments represents a long-term source of bacteria to streams. Current capability, potential advances, and limitations of this model framework for assessing pathogen transmission risks will be discussed. Because the transport model is probabilistic, it is amenable to incorporation into risk models, but a lack of characterization of key microbial processes in sediments and benthic biofilms hinders current application.