Autocalibration of Chlorine Transport Model for Steady State Distribution System by Genetic Algorithm

The chlorine reaction kinetics within a distribution system is affected by the reactions occurring in the bulk flow in a pipe and at the pipe wall. The field determination of parameters governing the wall reactions of a pipe is difficult and hence these are a product of calibration. The autocalibration of a chlorine transport model consists of estimating these unknown parameters by comparing the measured and simulated chlorine concentrations at the monitoring nodes within the distribution system in a least square sense. The inverse model presented in the paper determines these unknown parameters by simulation-optimization procedure in which the Genetic Algorithm technique is used as an optimization module. The verification and application of the developed inverse model are illustrated using a large multiple source water distribution system under steady state. The developed inverse model is useful to the water supply agencies for calibration of the chlorine transport model for a water distribution system and hence to improve the operational strategies to maintain chlorine residuals within the system.