Water distribution systems (WDSs) are subject to operational changes due to variability in demands, the availability of flow rates, system maintenance and unexpected events. This study aims to assess the behavior of water quality in a distribution network associated with operational changes that the system typically undergoes. For this work, two black-box models were compared to predict chlorine concentration at different nodes in a small network and a large network. The model was trained with synthetic data from simulations through the EPANET-Python Toolkit. The results show that the black-box model can be implemented to predict water quality in real time.