Uncertainties in stormwater E. coli levels.

Although water-quality monitoring programs have been widely used to identify and understand the level of pollution in urban stormwater systems, these data are often used without due consideration of the inherent uncertainties contained within these measurements. This study focuses on the uncertainties associated with the monitored levels of Escherichia coli, a common microbial indicator, in urban stormwater. Four sites located in Melbourne, Australia, were used to assess the uncertainty of six stormwater flow and E. coli variables: (1) discrete E. coli concentration, (2) stormwater flow rate, (3) stormwater event volume, (4) event mean concentration (EMC) of E. coli (i.e. a flow-weighted average of an event's E. coli concentrations), (5) E. coli load for each measured event, and (6) site mean E. coli concentration (SMC) (i.e. a volume-weighted average of the E. coli EMCs). Uncertainties of discrete E. coli samples were greater than 30%, while the uncertainty in stormwater flow measurements averaged greater than 97%, mainly due to the high uncertainties in measurements of very low flows. Propagation of these uncertainties, through their respective formulas, found that E. coli EMC uncertainties varied between 10% and 52% and that uncertainties relating to SMC estimates ranged from 35% to 55%. These results show the importance of considering uncertainty when using monitored data sets for any application, including those relating to stormwater management decisions. Suggestions are made about how to increase the accuracies of E. coli monitoring in urban stormwater and how to balance the different sources of uncertainties so that the overall combined uncertainties are minimised while keeping costs at a minimum.