In order to replace traditional sampling and analysis techniques, turbidimeters can be used to estimate TSS concentration in sewers, by means of sensor and site specific empirical equations established by linear regression of on-site turbidity T values with TSS concentrations C measured in corresponding samples. As the ordinary least-squares method is not able to account for measurement uncertainties in both T and C variables, an appropriate regression method is used to solve this difficulty and to evaluate correctly the uncertainty in TSS concentrations estimated from measured turbidity. The regression method is described, including detailed calculations of variances and covariance in the regression parameters. An example of application is given for a calibrated turbidimeter used in a combined sewer system, with data collected during three dry weather days. In order to show how the established regression could be used, an independent 24 hours long dry weather turbidity data series recorded at 2 min time interval is used, transformed into estimated TSS concentrations, and compared to TSS concentrations measured in samples. The comparison appears as satisfactory and suggests that turbidity measurements could replace traditional samples. Further developments, including wet weather periods and other types of sensors, are suggested.
Skip Nav Destination
Article navigation
Research Article|
December 01 2004
TSS concentration in sewers estimated from turbidity measurements by means of linear regression accounting for uncertainties in both variables Available to Purchase
J.-L. Bertrand-Krajewski
1URGC, INSA de Lyon, 34 avenue des Arts, 69621 Villeurbanne cedex, France
E-mail: [email protected]
Search for other works by this author on:
Water Sci Technol (2004) 50 (11): 81–88.
Citation
J.-L. Bertrand-Krajewski; TSS concentration in sewers estimated from turbidity measurements by means of linear regression accounting for uncertainties in both variables. Water Sci Technol 1 December 2004; 50 (11): 81–88. doi: https://doi.org/10.2166/wst.2004.0674
Download citation file:
Sign in
Don't already have an account? Register
Client Account
You could not be signed in. Please check your email address / username and password and try again.
Could not validate captcha. Please try again.
eBook
Pay-Per-View Access
$38.00