Real time control (RTC) is increasingly seen as a viable method to optimise the functioning of wastewater systems. Model exercises and case studies reported in literature claim a positive impact of RTC based on results without uncertainty analysis and flawed evaluation periods. This paper describes two integrated RTC strategies at the wastewater treatment plant (WWTP) Eindhoven, the Netherlands, that aim to improve the use of the available tanks at the WWTP and storage in the contributing catchments to reduce the impact on the receiving water. For the first time it is demonstrated that a significant improvement can be achieved through the application of RTC in practice. The Storm Tank Control is evaluated based on measurements and reduces the number of storm water settling tank discharges by 44% and the discharged volume by an estimated 33%, decreasing dissolved oxygen depletion in the river. The Primary Clarifier Control is evaluated based on model simulations. The maximum event NH4 concentration in the effluent reduced on average 19% for large events, while the load reduced 20%. For all 31 events the reductions are 11 and 4% respectively. Reductions are significant taking uncertainties into account, while using representative evaluation periods.@en

While the general principles and modelling approaches for integrated management/modelling of urban water systems already present a decade ago still hold, in recent years aspects like model interfacing and wastewater treatment plant (WWTP) influent generation as complements to sewer modelling have been investigated and several new or improved systems analysis methods have become available. New/improved software tools coupled with the current high computational capacity have enabled the application of integrated modelling to several practical cases, and advancements in monitoring water quantity and quality have been substantial and now allow the collecting of data in sufficient quality and quantity to permit using integrated models for real-time applications too. Further developments are warranted in the field of data quality assurance and efficient maintenance@en

This project aims at finding cost-efficient sets of measures to meet the Water Framework Directive (WFD) derived goals for the Dommel River (The Netherlands). Within the project, both acute and long-term impacts of the urban wastewater system on the chemical and ecological quality of the river are studied with a monitoring campaign in the urban wastewater system (wastewater treatment plant and sewers) and in the receiving surface water system. An integrated model, which proved to be a powerful tool to analyse the interactions within the integrated urban wastewater system, was first used to evaluate measures in the urban wastewater system using the existing infrastructure and new real-time control strategies. As the latter resulted to be beneficial but not sufficient, this paper investigated the use of additional infrastructural measures to improve the system cost-effectively and have it meet the Directive's goals. Finally, an uncertainty analysis was conducted to investigate the impact of uncertainty in the main model assumptions and model parameters on the performance robustness of the selected set of measures. Apart from some extreme worst-case scenarios, the proposed set of measures turned out to be sufficiently robust. Due to the substantial savings obtained with the results of this project, the pay-back time of the whole monitoring and modelling work proved to be less than 5 months. This illustrates the power of mathematical modelling for decision support in the context of complex urban water systems@en

Modeling of integrated urban water systems (IUWS) has seen a rapid development in recent years. Models and software are available that describe the process dynamics in sewers, wastewater treatment plants (WWTPs), receiving water systems as well as at the interfaces between the submodels. Successful applications of integrated modeling are, however, relatively scarce. One of the reasons for this is the lack of high-quality monitoring data with the required spatial and temporal resolution and accuracy to calibrate and validate the integrated models, even though the state of the art of monitoring itself is no longer the limiting factor. This paper discusses the efforts to be able to meet the data requirements associated with integrated modeling and describes the methods applied to validate the monitoring data and to use submodels as software sensor to provide the necessary input for other submodels. The main conclusion of the paper is that state of the art monitoring is in principle sufficient to provide the data necessary to calibrate integrated models, but practical limitations resulting in incomplete data-sets hamper widespread application. In order to overcome these difficulties, redundancy of future monitoring networks should be increased and, at the same time, data handling (including data validation, mining and assimilation) should receive much more attention.@en