Inferring the stochasticity associated with modeling the biological stability of drinking water within distribution networks

Post-treatment, drinking water is far from sterile, so microbial regrowth occurs, and the distribution pipes behave like a dynamic ecological niche for microbes. Unwarranted microbial regrowth within distribution pipes can lead to quality issues and health concerns. The application of computer-based tools adept at mechanistically simulating the dynamics of heterotrophic bacteria within distribution pipes is a practical approach to safeguarding biological stability during drinking water distribution systems (DWDS) operation. The imperfect understanding of most of the stochastic processes related to the heterotrophic bacterial dynamics and the natural randomness of the system constraints make mechanistic modeling complicated. Within the context of the current state-of-the-art, the questions on the level of detailing in describing the processes within the pipe domain for mechanistically describing the microbiological quality with a certain acceptable level of accuracy are still unanswered. In this regard, we attempt to answer these questions and overcome the limitations of the state-of-the-art to develop a practically relevant modeling tool for DWDS management. The specific objectives of this study are to (1) develop stochastic mechanistic models considering the three-level uncertainties – model parameters (kinetic rate constants), model coefficients (dispersion coefficient), and state variables (source quality characteristics) – along with the uncertainties in the system hydraulics for predicting microbiological quality fluctuations in DWDS; (2) understand the level of complexity that needs to be integrated into modeling to explain the water quality dynamics correctly; (3) present the applicability of the developed models for simulating microbiological quality fluctuations in a real-world DWDS.