This work presents a methodology to efficiently calibrate chlorine decay models. The calibration consists in estimating the unknown parameters by comparing the measured and simulated chlorine concentrations at the monitored nodes within the distribution system in a least square sense using a normalized quadratic cost function. Since this function involves a non- explicit expression of the model, a genetic algorithm (GA) is applied to optimize the model parameters by minimizing the difference between the model-predicted values and the field-measured ones. The method is applied to a part of the Barcelona drinking water network.