Real Time Predictive Modeling for Public Water Quality Alerts

Combined sewer overflows (CSOs) and their associated pollution loadings to water bodies continue to be a primary focus for wastewater utilities across the country. Bacteria loadings from CSOs, as measured by concentration of E. coli for freshwaters and Enterococci for marine waters, have been deemed detrimental for human recreation by the U.S. EPA and draw negative attention from effected communities (U.S. EPA, 2012). In Massachusetts (MA), utilities are required to issue electronic alerts via email and/or websites when a CSO event happens in their community. While this information establishes a basis for public awareness of potential risks, it does not necessarily translate into the duration of potential risks after an overflow, or the locations where elevated bacteria levels might be found. This study's objective was to develop a real time predictive model of bacteria loadings resulting from 5 cities' CSOs to the Merrimack River (Manchester and Nashua, NH; Lowell, Lawrence, and Haverhill, MA). Specifically, this included the implementation of an innovative daily alert program to inform the general public, through virtual means, about the potential swimming and boating hazards in the Merrimack River at Newburyport, MA from bacterial pollutants resulting from CSOs. The locations of the CSOs and alert focus area are shown in Figure 1.