Water engineering and management practices strongly evolved during recent years. More focus is given to integration of civil technical, hydrological, water quantity and quality, ecological and other aspects. However, this integration is to date not as efficient as it should be. This has both institutional and technical reasons. At the technical level, mathematical models are used as decision support tools, but are most often developed for individual water subsystems (rivers, sewer systems, ...) and allow only limited number of unisectorial scenario investigations to be carried out (floods, low flows, water quality, ...) mostly due to their large calculation times. Consequently, water management decisions are based on scenario investigations that consider only a limited number of interactions, far more limited than what is needed to enable 'real' integrated water resources management.
The main objective of this study is to improve the scientific knowledge and understanding of the processes that affect the river water quantity and quality through considering the natural system, the human environment and the complex interactions between both in an integrated way. More specifically, a water quality model for both the sewer system and the river system is set up. The first is based on a data driven approach since the current knowledge of the system does not allow the build up of a detailed physically based model. The latter is based on a conceptualization of a current state-of-the-art detailed, physically based river water quality model namely MIKE11-ECO Lab. Both models focus on short calculations times allowing uncertainty and sensitivity analysis and integration with other subsystems into one holistic model. The model is implemented and the impact of the sewer system on the river system is studied for the Grote Nete catchment, a moderately urbanized Belgian river catchment.