Variability of Effluent Quality in a Multi

Weber B. and Juanico M. (1990). Variability of Effluent Quality in a Multi-step Complex for Wastewater Treatment and Storage. Wat. Res, 24(6):765-771.

ABSTRACT

The present paper deals with the variability of effluent quality in a complex for wastewater treatment and storage. The complex is made up of several steps:
an intensive sewage treatment plant followed by a two-cell stabilization reservoirs and an operational reservoir in series. The generally held notion that wastewater treatment units reduce inflow quality variability stem from the wrong use of Standard Deviation to compare data of different magnitude. The Standard Deviation is a statistic that describes the variability of data in ABSOLUTE terms. It is not appropriate to compare outflow and inflow quality variability in a treatment plant, since outflow quality values are usually several times lower than inflow ones. The same problem arises when comparing different parameters (e.g., the variability of pH with the variability of BOD). In these cases it is necessary to describe the variability of data in RELATIVE terms. The Coefficient of Variation (CV) is used in this work to describe the variability of each single quality parameter at each step of the Kishon Complex. There are conspicuous differences in variability between the wastewater quality parameters. These differences can help for a better selection of parameters for both monitoring and modelling purposes, as well as for determination of differential sampling frequencies in monitoring programs. The different steps of the treatment complex hardly differ in the variability of effluent quality as a whole, expressed as the average CV of all parameters in each step. Wastewater quality variability is only partially transmitted along the complex, but local born disturbance maintains the total amount of variability at each step almost unchanged. Control and reduction of variability at one step of the complex will not significantly affect the amount of variability in the subsequent steps.

KEYWORDS

modelling, monitoring, sampling design.