Effect of sewage sampling frequency on determination of design parameters for municipal wastewater treatment plants

The uncertainty associated with the determination of load parameters, which is a key step in the design of wastewater treatment plants (WWTPs), was investigated on the basis of data sets from 58 WWTPs. A further analysed aspect was the organic load variations associated with variable sewage temperatures. Data from 26 WWTPs with a high inflow sampling frequency was used to simulate scenarios to investigate the effect of lower sampling frequencies through a Monte Carlo approach. The calculation of 85-percentile values for chemical oxygen demand (COD) loadings based on only 26 samples per year is associated with a variability of up to +/- 18%. Approximately 90 samples per year will be necessary to reduce this uncertainty for estimation of COD loadings below 10%. Hence, a low sampling frequency can potentially lead to under- or overestimation of design parameters. Through an analogous approach, it was possible to identify uncertainties of +/- 11% in COD loading when weekly average data was used with four samples per week. Finally, a tendency to lower COD input loads with increasing temperatures was identified, with a reduction of about 1% of the average loading per degree Celsius.

Automated summary

The study investigated the uncertainty associated with load parameters in the design of wastewater treatment plants, especially in relation to organic load variations with changing sewage temperatures. Lower sampling frequencies can lead to under- or overestimation of design parameters, showing a variability of up to +/- 18% with only 26 samples per year for COD loadings. Increasing the number of samples to approximately 90 per year can help reduce this uncertainty for estimation of COD loadings below 10%.