Modelling water quality for water distribution systems

Abstract

Maintaining water quality in distribution systems has become a prominent issue in the study of water networks. This thesis concentrates on disinfectant and particle counts as two important indicators of water quality. The models discussed in this work are based on data collected by the author. The experimental set-up and procedure are described and observations of particle counts, particle counter size distributions, monochloramine as disinfectant, temperature, heterotrophic plate counts and epifluorescence microscopy counts are reported. A model of the response of particle counts to an increase in flow is developed. This model is obtained from specification derived from the data and assumptions, and is validated by its interpretability and its fit to data. A local shear-off density and an initial biofilm shedding profile were introduced and thus a linear model for this part of the water quality dynamics could be obtained. A procedure for the identification of the parameters of the local shear-off function and for the determination of the biofilm shedding profile is presented. This profile can be used to provide information about the status of the distribution system in terms of shear-off from the biofilm on the pipe walls. Monochloramine decay dynamics are investigated. The chlorine meter data is preprocessed with the help of titration data to correct meter drift. The data is then used in calibrating two different possible chlorine models: a model with a single decay coefficient and a model with bulk decay coefficient and wall demand (as used in Epanet). Important difficulties in identifying these parameters that come about because of the structure of the models are highlighted. Identified decay coefficients are compared and tested for flow, inlet chlorine and temperature dependence. The merits and limits of the approach to modelling taken in this work and a possible generalisation are discussed. The water industry perspective and an outlook are provided.