The KALLISTO project aims at finding cost-efficient sets of measures to meet the Water Framework Directive (WFD) derived goals for the river Dommel. 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 an integral monitoring campaign in the urban wastewater system (WWTP and sewers) and in the river. Based on this monitoring campaign, detailed models were calibrated. These models are partly simplified and integrated in a single model, which is validated using the detailed submodels. The integrated model was used to study the potential for impact-based real-time control (RTC). Impact based RTC proved to be able to improve the quality of the receiving waters significantly, although additional measures remain necessary to be able to meet the WFD requirements

The Kallisto project aims at finding cost effective sets of measures to meet the WFD derived goals for the river De Dommel. The project reasons from the both acute and long term impacts of the urban wastewater system on the quality and ecology of the river that are studied with an integral monitoring campaign in the wastewater system (WWTP and sewers) and river. By applying impact based RTC, the project aims at minimizing additional investments in infrastructure while meeting the requirements. Moreover, uncertainty is explicitly considered in the optimization and decision making process. The paper describes the overall project strategy, some preliminary results of modelling and monitoring of the components of the urban water system and the demonstration research for treatment techniques and the planned integration into optimization and decision making.

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.

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The KALLISTO project aims at finding cost-efficient sets of measures to meet the Water Framework Directive (WFD) derived goals for the Dommel River (The Netherlands). An integrated model, which showed to be a powerful tool to analyze 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 RTC strategies. As the latter resulted to be beneficial but not sufficient, this contribution investigates the potential benefit of additional infrastructural measures to improve the system cost-effectively and have it meet the WFD goals and this using an integrated perspective. Finally, a scenario 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 and significantly more cost-effective compared to using a more traditional non-integrated approach.