This study aims at the development of an optimization model based on a model calibration, using artificial immune systems (AIS) for quantifying and locating water loss in water distribution networks (WDNs) without using observed pressure data as used by previous studies in the related literature. The modified Clonal Selection Algorithm (modified Clonalg), a class of AIS, was used as a heuristic optimization technique in the model. EPANET 2, a widely known WDN simulator, was used in conjunction with the model. The model was applied to four-loop and six-loop virtual WDNs under steady-state conditions in order to test its performance in water loss detection in both pipes and nodes. Also, sensitivity analysis of the modified Clonalg was performed according to mutation coefficient to test its search capability in this optimization problem. The results showed that the model appeared to be promising in terms of water loss detection in WDNs.

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