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

Abstract

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.