INFRASTRUCTURE DISTRIBUTIONS CONTROL SPATIAL AND TEMPORAL TRENDS IN MUNICIPAL WATER INPUTS ACROSS AN URBAN WATERSHED

Urban expansion increases the demand for drinking water and the production of wastewater. Both the accidental and intention release of these municipal water types, via lawn irrigation (drinking water), treatment plant discharges or sewer overflows (wastewaters), or leaking infrastructure (both water types), can impact stream water chemistry. While previous studies have estimated municipal water inputs to surface waters, little work has been done to understand how their contributions integrate across catchments in space and time. Thus, this study used high resolution spatial and temporal sampling in an urban watershed (Deer Creek near Saint Louis, Missouri, United States) to identify how municipal waters vary from the stream’s headwaters to the mouth. We used tracers unique to drinking water (F) and wastewater (B and optical brighteners (OB)) to characterize municipal water inputs. Spatial samples were collected bimonthly at 17 sites across the 19.4 km² catchment. To understand seasonal changes, we obtained both weekly baseflow and high frequency flood samples from the mouth of the catchment. Samples were analyzed for B and OB levels; ongoing work will characterize F concentrations. The B concentrations ranged from 32 to 95 μg/L and OB levels ranged from 10.8 to 38.0 RFU for Deer Creek, which are intermediate values for B and OB among the rural stream (29 μg/L and 3.7 RFU), drinking water (82 μg/L and 5.5 RFU), and wastewater (212 μg/L and 105 RFU) end-members in the region. A three-component mixing model using B and OB values showed that drinking water contributions (26 ± 21%) to Deer Creek were greater than wastewater inputs (7 ± 6%), which is likely the result of drinking water leaking from pressurized pipes. Initial results suggested that the spatial distribution of municipal waters across the catchment was strongly controlled by infrastructure density. Weekly grab sample data revealed that, during low flow conditions, B and OB did not vary over time. However, during a flood response, we observed a peak in OB values that lagged the discharge peak. We calculated that 6% of the total flood discharge was comprised of wastewater that probably originated from an upstream sewer overflow. High resolution spatial and temporal data for municipal water contributions at the catchment scale can inform future mitigation strategies.