AWWA ACE59927

The first generation of mechanistic models of bacterial regrowth in distribution systems (DS)provides insight into cause and effect relationships. However, the state of knowledge about theprocesses included in these models is insufficient to warrant deterministic predictions. Even ifthe process descriptions are reasonable, the uncertainty in values of key system constants limitspredictions of bacterial growth. A new mechanistic model was developed to incorporate theaccepted knowledge of physical, chemical and biological processes with the hydraulic features in order to capture the unsteady state behavior of the DS. Sensitivity testing showed thatrate constants for chlorine decay reactions in bulk water and on the pipe wall as well as themaximum growth rate constant of attached bacteria are the most important parameters. A simplehypothetical network was used to test evaluate the effects of uncertainty in these three systemconstants by running 100 Monte Carlo simulations. Cumulative probability plots (CPP) showedthat a wide range of predictions for concentrations of bacteria and chlorine in bulk water atvarious nodes in the DS. The magnitude of these concentrations and the range of values weregreatly affected by water residence time to each node. Once the chlorine residual is depleted,bacterial growth is mainly influenced by the amount of substrate available. However, highvalues of maximum growth rate coefficient of attached bacteria and bulk and wall decaycoefficients did not necessarily lead to the maximum bacterial growth at a given sampling site. Includes 18 references, tables, figures.



Keywords: Modeling; Bacteria; Chlorine; Chemicals; Sampling; Testing; Distribution Systems