Real time control to manage sewer systems

The aim of this work is mainly the real time forecast of pollutant loads in an urban sewer network. The method used in this study is based on two implements: the rating curve and the Kalman filter. The rating curve model is used to substantiate the correlation between pollutant loads and runoff. The assumption of systematic synchronism between hydrograph and pollutograph peaks constitutes however a weakness of this model, which we propose to overcome within the framework of this work. The rating curve model is therefore modified by the introduction of a term that takes into account the lag identified in real time. In addition, the constancy of the parameters of the classical rating curve model constitutes another weakness when phenomena need to be reproduced during a same event or from one event to another. In order to overcome this second weakness, the Kalman filter was used to identify the parameters of a dynamic model according to the errors of forecast noted at each time step. The method was tested successfully on sector I of the town of Verdun (Quebec).