Hydrodynamic modelling of microbial water quality in drinking water sources

Abstract: The faecal contamination of water sources can cause waterborne disease outbreaks among drinking water consumers. To design drinking water treatment and minimise consumer health risks, knowledge on source water quality is needed. The aim of this thesis was to describe the microbial water quality in water sources in order to facilitate the provision of safe drinking water. In this thesis, hydrodynamic modelling, microbial source tracking (MST), and quantitative microbial risk assessment (QMRA) were combined to study two surface drinking water sources, Lake Rådasjön and the river Göta älv in Sweden. The microbial water quality in these water sources was successfully characterised by the developed hydrodynamic models. The results demonstrated that the concentrations of faecal indicators and pathogens in these water sources vary and are event-driven. In the lake, the contaminant transport was strongly affected by wind conditions and by the vertical temperature stratification; in the river, the contaminant transport was driven by the water flow. Both for the lake and river, human faecal sources were the main contributors to the contamination at the water intakes. Based on the obtained results, recommendations for the management of the microbial risks concerning the studied water sources were formulated. It can be concluded that hydrodynamic modelling is a very useful approach to describe and predict the microbial water quality in drinking water sources. In this thesis, hydrodynamic modelling was successfully applied to study the factors that affect the contaminant spread in the water source, to capture the spatial and temporal variability of the microbial water quality, to provide short-term forecasts, and to test hypothetical scenarios. Furthermore, the results of the hydrodynamic modelling improved the interpretation of the MST data and provided input for QMRA. The novelty of this thesis lies in using hydrodynamic modelling in combination with MST and QMRA, in order to enhance the applicability and output of each individual approach, and to describe and predict the microbial water quality in drinking water sources.