Assessment of sampling strategies for estimation of site mean concentrations of stormwater pollutants
Résumé
The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban
water management. In order to determine effective sampling strategies for estimating pollutant concentrations,
data from extensive field measurements at seven different catchments was used. At all sites,
1-min resolution continuous flow measurements, as well as flow-weighted samples, were taken and
analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli (E. coli). For each of these
parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The
measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs
for each parameter, at each site. 17 different sampling strategies, including random and fixed strategies
were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/
measured SMCs were further analysed to determine the most effective sampling strategies. Results
indicate that the random sampling strategies were the most promising method in reproducing SMCs for
TSS and TN, while some fixed sampling strategies were better for estimating the SMC of E. coli. The
differences in taking one, two or three random samples were small (up to 20% for TSS, and 10% for TN and
E. coli), indicating that there is little benefit in investing in collection of more than one sample per event if
attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average
of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence
interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The
coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90%
confidence interval ratio of the estimated/measured SMCs (R2 = 0.49; P < 0.01) as well as the number of
events required to achieve certain accuracy, and hence could be a promising surrogate for determining
the sampling frequency needed to accurately estimate SMCs of pollutants.