Municipal separate storm sewer system (MS4) dry weather flows and potential flow sources as assessed by conventional and advanced bacterial analyses.

Municipal separate storm sewer systems (MS4s) function in urbanized areas to convey flows during both wet weather (i.e., stormwater) and dry weather (i.e., urban runoff as well as subsurface sources of flow) to receiving waters. While urban stormwater is known to contain microbial and chemical pollutants, MS4 dry weather flows, or non-stormwater discharges (NSWDs), are much less studied, although they are also known to contain pollutants, especially when these flows include raw sewage. In addition, some natural NSWDs (e.g., from groundwater infiltrating MS4 pipes) are critical for aquatic habitat protection. Thus, it is important to distinguish NSWD sources to prevent non-natural flows while retaining natural waters (i.e., groundwater). Here, MS4 dry weather flows were assessed by analyzing water samples from MS4 outfalls across multiple watersheds and water provider service areas in south Orange County, CA; potential NSWD sources including sewage, recycled water, potable water, and groundwater were sampled and analyzed for their likely contributions to overall NSWDs. Geochemical and microbiological water quality indicators, as well as bacterial communities, differed across NSWDs, yet water quality within most locations did not vary significantly diurnally or by sampling date. Meanwhile, NSWD source waters had distinctly different bacterial taxa abundances and specific bacterial genera. Shared geochemical and microbial characteristics of certain sources and outfall flows suggested the contributions of sources to outfall flows. The average proportions by sources contributing to MS4 outfalls were further estimated by SourceTracker and FEAST, respectively. The results of this study highlight the use of multiple tools when assessing chemical and microbiological water quality to predict sources of NSWDs contributing to urban MS4 flows during dry weather. This information can be used to support management actions to reduce unnatural and high risk sources of dry weather drainage while preserving natural sources important to environmental health in downstream receiving waters.

Assessing urban runoff program progress through a dry weather hybrid reconnaissance monitoring design.

Characterizing dry weather conditions in urban Municipal Separate Storm Sewer Systems (MS4s), and then prioritizing and addressing problems due to urban pollutants, is a daunting challenge. The size and complexity of most MS4s and the ephemeral nature of many dry weather problems hamper efforts to identify and eliminate pollutant sources, and to track trends in condition. As a result, assessing overall program progress has proven difficult. We describe a hybrid dry weather urban monitoring design from southern California that combines probabilistic and targeted sampling to rigorously identify and prioritize problems and track program progress. Data from probabilistic sites define the urban background and establish tolerance intervals, which identify sites that persistently exceed the overall urban background. Targeted sites focus on locations where nearby activities and/or past history suggest that pollutant levels will be elevated. Embedding targeted monitoring within a probabilistic design enables data from targeted sites to be interpreted in a more meaningful regional context. Data from all sites are also used to construct site- and pollutant-specific control charts. These charts quickly identify instances where a site's behavior significantly changes, compared to its past behavior, suggesting an active source in the upstream drainage area. The hybrid design, and the use of formal statistical tools (tolerance intervals and control charts), permit the program to systematically prioritize problematic sites, compare conditions to the regional urban background, and track trends over time. In addition, the program's design allows several measures of program progress to be defined and thus consistently followed over time. Such hybrid designs can provide substantial advantages compared to more traditional monitoring approaches.