<p><strong>Abstract.</strong> The role of a water drinking distribution network (WDDN) is to supply high-quality water at the necessary pressure at various times of the day for several consumption scenarios. Locating and identifying priorities of water leakage areas becomes major preoccupation for manager of the water supply, to optimize and improve constancy of supply. In this paper, we present the results obtained on the field from a research conducted in order to identify

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... d to locate leaks in (WDDN) focused on the resolution of the Fixed And Variable Area Discharge (FAVAD) equation by use of the prediction algorithms in conjunction with hydraulic modeling and the Geographical Information System (GIS). The leak localization method is applied in the oldest part of Casablanca. We have used, in this research, two methodologies in different leak episodes: (i) The first episode is based on a simulation of artificial leaks on the MATLAB platform using the EPANET code to establish a database of pressures that describe the network's behaviour in the presence of leaks. The data thus established has fed into a machine learning algorithm called Random Forest, which will forecast the leakage rate and its location in the network; (ii) The second was field-testing a real simulation of artificial leaks by opening and closing of hydrants, on different locations with a leak size of 6 l/s and 17 l/s. Results are similar for both methods, the location of leaks is found within 100 meters from the actual leaks.</p>