Using a multi-tracer approach to assess wastewater contaminant inputs to surface waters from onsite wastewater treatment systems

Quantifying contaminant inputs from onsite wastewater treatment systems (OWTS) to surface waters is needed in many watersheds to inform water quality management programs. This quantification is challenging due to the distributed locations of OWTSs across rural watersheds and uncertainties regarding the fate of the various wastewater contaminants in the environment. The objectives of this study were to i) identify the dominant pathways via which contaminants from OWTS reach streams, and ii) evaluate whether contaminant loads reaching streams from OWTS varies between watersheds with different physical and socio-economic characteristics, and between dry and wet weather conditions. These objectives were addressed by combining geospatial mapping, field investigations, and statistical analyses with the study focused on watersheds in Ontario, Canada. Detailed stream sampling was conducted in four watersheds with human wastewater tracers including artificial sweeteners (acesulfame, saccharin, cyclamate, sucralose) and microbial source tracking markers (HF183 and human mitochondrial markers) used to untangle the pathways via which OWTS-derived contaminants may be transported to streams. In addition, widespread sampling was conducted across 53 watersheds to assess the influence of physical and socio-economic characteristics on OWTS-derived contaminant inputs to streams. The data indicate that more contaminants reach streams during wet weather conditions and contributing pathways include groundwater transport as well as more rapid pathways including residential and agricultural tile drains. For more conservative contaminants, the amounts of contaminants reaching streams were significantly higher in watersheds with older households and with low topographic wetness index, but for less conservative contaminants other factors including the distance between OWTS and streams may be important. The findings of this study are needed to inform OWTS best management practices and to improve contaminant load estimates to streams.