The effective environmental management of combined sewer systems requires reliable estimation of discharge and pollutant loads conveyed at the outlet during rainstorms. This study investigates how, with a lumped modelling approach, it is possible to reproduce the quality characteristics of discharged water, provided that high temporal resolution experimental data of pollutant concentrations are available. The methodology is applied to the combined sewer of a real urban drainage network where a continuous high resolution monitoring campaign of water quality and quantity has been carried out at an overflow structure location near the outlet of the drainage system. The lumped modelling approach has been implemented in the Storm Water Management Model (SWMM) with hydrological parameters estimated from cartographic information, based on recently proposed methodology that allows reliably simulating the storm hydrographs without model calibration. A semi-distributed model has been also developed using the SWMM with hydrologic parameters randomly sampled to fit the measured hydrographs of different training and validation data. The results obtained show that the uncalibrated lumped model simulates the observed hydrographs with similar performance as with the semi-distributed model (i.e., the normalized Nash-Sutcliff efficiency index of the validation set is 0.753 for the uncalibrated lumped model and 0.765 for the best-performing sampled parameter set of the semi-distributed model). The water quality parameters describing the build-up and wash-off of total dissolved solids (TDS) in a lumped model have been calibrated too, as well as those describing the mixing and consumption of dissolved oxygen (DO). The results show that a lumped modelling approach can reproduce the water quality dynamics in a combined sewer system, representing a promising tool for effective environmental management. However, event-specific calibrated parameter values have been obtained in some cases, which require further investigation and still limit the general applicability of the obtained results, thus confirming that setting up a reliable model requires water quality measurements.

The management of an Urban Drainage System (UDS) is a complex task, as it requires extensive knowledge about precipitation regime, hydrological features of the catchment, hydraulic characteristics of the drainage network, and information about the water use by the served inhabitants. Complex semi-distributed hydrological and physically based hydraulic models are nowadays available to summarise such information and run simulations. However, in many cases, the uncertainty of the available hydrological information hampers the use of complex models. Hence, simple models with few parameters and small computational effort may be preferable, especially for UDS management problems requiring the execution of many simulations. This paper proposes a convenient approach to define effective lumped Simplified Models (SMs) of UDSs, the parameters of which can be estimated directly from cartographic information. For several case studies of UDS with different morphological and topological characteristics, SMs were built, capable of reproducing the hydrographs provided by available semi-distributed Detailed Models (DMs), assumed as benchmark in absence of measured hydrographs. To this aim, the SWMM simulation software was used, and the SM lumped parameters were calibrated by maximising the goodness of fit between the hydrograph of the DM and of the SM. The results show that SMs satisfactorily predict the hydrographs for all the case studies, and that robust relationships between the calibrated parameters and morphological and topological characteristics of the UDS can be established. This suggests that SMs can be used by decision makers for preliminary design, planning studies and management problems of UDSs, as their parameters can be soundly estimated from cartographic information. An example of application of SMs to Combined Sewer Overflow prediction is also presented.

In water networks characterized by a significant variation in ground elevations the necessity of pumping water in some areas is complicated by a conflicting requirement to reduce excess pressures in other areas. This and the increasing cost of electricity has led to the use of Pumps-operating-As-Turbines (PATs) devices that can reduce pressure (and leakage) whilst harvesting energy. This paper presents a methodology for optimal water distribution system (WDS) management, driving the optimization by minimizing the surplus pressure at network nodes and the operational pumping costs and maximizing the income generated through energy recovery. The method is based on a highly parallelized Evolutionary Algorithm, employing an hydraulic solver to evaluate hydraulic constraints. Water demands at network nodes are considered as uncertain variables modelled by using a probabilistic approach in order to take into account unknown future demands. The approach is demonstrated in different case studies. Results obtained highlight that the economic benefits of installing PATs for energy recovery in conjunction with a combined pump-scheduling and pressure management regime is especially related to the input network characteristics. Further analysis of the importance of the probabilistic approach and of the influence of the interval time step adopted for the optimization has been evaluated.