An assessment of static and dynamic models to predict water treatment works performance

Abstract

The relative accuracy of static and dynamic water treatment works (WTWs) models was examined. Case study data from an operational works were used to calibrate and verify these models. It was found that dynamic clarification, filtration and disinfection models were more accurate than static models at predicting the final water quality of an operational site but that the root mean square errors of the models were within 5% of each other for key performance criteria. A range of abstraction rates at which the WTWs was predicted to operate adequately were identified using both types of models for varying raw water qualities. Static clarification, filtration and disinfection models were identified as being more suitable for whole works optimisation than dynamic models based on their relative accuracy, simplicity and computational demands.