Stormwater biofilters are not currently optimised for pathogen removal since the behaviour of these pollutants within the stormwater biofilters is poorly understood. Modelling is a common way of optimising these systems, which also provides a better understanding of the major processes that govern the pathogen removal. This paper provides an overview of a laboratory-scale study that investigated how different design and operational conditions impact pathogen removal in the stormwater biofilters. These data were then used to develop a modelling tool that can be used to optimise the design and operation of the stormwater biofilters. The model uses continuous simulations where adsorption and desorption were dominant during wet weather periods and first order die-off kinetics were significant in dry periods between the wet weather events. Relatively high Nash Sutcliffe Efficiencies (>0.5) indicate that the calibrated model is in good agreement with observed data and the optimised model parameters were comparable with values reported in the literature. The model's sensitivity is highest towards the adsorption process parameter followed by the die-off and desorption rate parameters, which implies that adsorption is the governing process of the model. Vegetation is found to have an impact on the wet weather processes since the adsorption and desorption parameters vary significantly with the different plant configurations. The model is yet to be tested against field data and needs to be improved to represent the effect of some other biofilter design configurations, such as the inclusion of the submerged zone.

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