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Data-mining analysis of in-sewer infiltration patterns: seasonal characteristics of clear water seepage into Brussels main sewers

par De Ville De Goyet, Nicolas ;Le, Hong Minh ;Schmidt, Ludovic ;Verbanck, Michel
Référence Urban Water Journal, 14, 10, page (1090-1096)
Publication Publié, 2017

Article révisé par les pairs

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Résumé :

Parasitic clear water infiltration is known to increase the waste water volumes in most sewerage systems. Amongst others, a problem arising from that is a significant variation of waste water pollutant concentration over time, which complicates the purification process and increases its cost. Capitalizing on new extensive databases, we propose a new method for the identification of clear water infiltration rates based on data-mining and data consolidation of long time data series. Based on a straightforward anthropogenic tracer, together with a simple but rigorous water budget, the infiltrated volumes are quantified day-by-day for the entire zone treated by a major waste water treatment plant. Brussels city is used as an example of the applicability of the method over several years, demonstrating the significant seasonal changes in sewer infiltration rates in the area and the progress achieved so far by structural sewer repair.