Wastewater flow forecasts are key components in the short- and long-term management of sewer systems. Forecasting flows in sewer networks constitutes a considerable uncertainty for operators due to the nonlinear relationship between causal variables and wastewater flows. This work aimed to fill the gaps in the wastewater flow forecasting research by proposing a novel wastewater flow forecasting model (WWFFM) based on the nonlinear autoregressive with exogenous inputs neural network, real-time, and forecasted water consumption with an application to the sewer system of Casablanca in Morocco. Furthermore, this research compared the two approaches of the forecasting model. The first approach consists of forecasting wastewater flows on the basis of real-time water consumption and infiltration flows, and the second approach considers the same input in addition to water distribution flow forecasts. The results indicate that both approaches show accurate and similar performances in predicting wastewater flows, while the forecasting horizon does not exceed the watershed lag time. For prediction horizons that exceed the lag time value, the WWFFM with water distribution forecasts provided more reliable forecasts for long-time horizons. The proposed WWFFM could benefit operators by providing valuable input data for predictive models to enhance sewer system efficiency.

Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many cities around the world. Model predictive control (MPC) systems offer a new approach to mitigate the impact of CSOs by generating optimal temporally and spatially varied dynamic control strategies of sewer system actuators. This paper presents a novel MPC based on neural networks for predicting flows, a stormwater management model (SWMM) for flow conveyance, and a genetic algorithm for optimizing the operation of sewer systems and defining the best control strategies. The proposed model was tested on the sewer system of the city of Casablanca in Morocco. The results have shown the efficiency of the developed MPC to reduce CSOs while considering short optimization time thanks to parallel computing.