Identifying Misconnection Hotspots Using Coliforms and Biofilm Communities

Abstract

Sewage misconnections currently pose severe threats to water quality especially in urban areas in the UK. These misconnections lead to the discharge of untreated wastewater into receiving watercourses via surface water outfalls. Regular discharges from this source could lead to these watercourses failing to meet standards set by the Water Framework Directives. Despite the impacts resulting from this urban diffuse pollutant source, research into this area is limited. The study area is the River Lee, which is known to experience issues with water quality especially within the heavily urbanized lower Lee section. Misconnections are one of the major contributors to the poor water quality status of the River. In this study, the Lee was investigated using several parameters. The approach involved the monitoring of coliform bacteria to detect outfalls where misconnections were likely, then biofilm samples below selected outfalls were used for both clean and polluted sites to look for community types. Results showed severe pollution within some sections of the River particularly within the lower Lee. Pymmes Brook was used as a case study, both coliform bacteria and biofilm communities below outfalls were further investigated for clean and polluted sites. Results from the Pymmes Brook study also showed that this watercourse was experiencing severe issues with water quality, with elevated levels of coliform bacteria identified below polluted outfalls. Biofilm community data obtained during the pilot and experimental phases of study were analyzed using a range of multivariate techniques. Results of the analysis showed consistent x patterns in community structure within sites with similar water quality, with indicator species identified. Communities below polluted outfalls were composed mainly of species tolerant of organic pollution thus indicating a response of communities to misconnection discharges. Currently, the identification of misconnections are carried out through trackbacks, a process which is expensive and time consuming. During this study an inexpensive and rapid approach is proposed for assessing misconnections within a catchment. Using this method, misconnection hotspots are mapped out using coliform bacteria and biofilm communities. Using catchment data and predicted coliform bacteria from enumerated counts, misconnections within these hotspots are assessed. Having tested this approach on Pymmes Brook, a tributary of the River Lee, the results obtained were promising. Pending further verification, this system provides an economical and rapid tool for the assessment of misconnections within a catchment.