Calculation of wastewater effluent leakage to pristine water sources by the weighted average of multiple tracer approach. Issue 5 (22nd May 2014)

• Record Type: Journal Article
• Authors: Gasser, Guy; Pankratov, Irena; Elhanany, Sara; Glazman, Hillel; Lev, Ovadia
• Is Part Of: Water resources research. Volume 50:Issue 5(2014:May)
• Page Start: 4269
• Page End: 4282
• Publication Date: 2014-05-22
• Subjects: Hydrology -- Periodicals; 333.91
• DOI: 10.1002/2013WR014377
• Languages: English
• ISSNs: 0043-1397

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>A methodology used to estimate the percentage of wastewater effluent in an otherwise pristine water site is proposed on the basis of the weighted mean of the level of a consortium of indicator pollutants. This method considers the levels of uncertainty in the evaluation of each of the indicators in the site, potential effluent sources, and uncontaminated surroundings. A detailed demonstrative study was conducted on a site that is potentially subject to wastewater leakage. The research concentrated on several perched springs that are influenced to an unknown extent by agricultural communities. A comparison was made to a heavily contaminated site receiving wastewater effluent and surface water runoff. We investigated six springs in two nearby ridges where fecal contamination was detected in the past; the major sources of pollution in the area have since been diverted to a wastewater treatment system. We used chloride, acesulfame, and carbamazepine as domestic pollution tracers. Good correlation (R<sup>2</sup> > 0.86) was observed between the mixing ratio predictions based on the two organic tracers (the slope of the linear regression was 1.05), whereas the chloride predictions differed considerably. This methodology is potentially useful, particularly for cases in which detailed hydrological modeling is unavailable but in which quantification of wastewater penetration is required. We demonstrate that the use of more than one tracer for estimation of the mixing ratio reduces the combined uncertainty level associated with the estimate and can also help to disqualify biased tracers.</p> </abstract>