The drinking water in the Netherlands is of high quality and the production cost is low. This is the result of extensive research in the past decades to innovate and optimise the treatment processes. The processes are monitored and operated by motivated and skilled operators and process technologists, which leads to an operator-dependent, subjective, variable and possibly suboptimal operation of the treatment plants. Furthermore, the extensive automation of the treatment plants reduces the possible operator attention to the individual process units. The use of mathematical process models might solve these problems. This thesis focuses on the application of models in model-based monitoring, optimisation and control of drinking-water treatment plants, with the Weesperkarspel treatment plant of Waternet as a case study. To shift the operation of drinking water treatment plants from experience driven to knowledge based, a model-based approach is shown to be effective. Models are successfully used in plant analysis and basic control design, resulting in the successful implementation of new basic control for the softening reactors at the Weesperkarspel plant. Model-based monitoring schemes abstract relevant information from the large amount of data and the schemes estimate the current state of the processes. Model-based control uses the monitored process state to dynamically optimise the treatment without introducing new disturbances in the treatment plant. Model-based optimisation gives the process technologist the possibility to improve treatment operation without disrupting the full-scale plant.