Data-driven methodological approach for modeling rainfall-induced infiltration effects on combined sewer overflow in urban catchments

International audience ; Combined sewer system deterioration poses significant challenges, especially as it leads to substantial volumes of Permanent Infiltration Inflow (PII) and Rain-Induced Infiltration (RII) to percolate into sewer pipes. This infiltration increases the risk of Combined Sewer Overflow (CSO) events and reduces the treatment plant's efficiency by diluting raw effluent. To effectively decrease CSO volumes, it is crucial to identify the various flow components and their contribution to overflow volumes. In this study, a data-driven hydrological model was developed, conceptualizing the surface hydrological processes as well as the interactions between soil water and the sewer system, based on long-term monitoring. Four flow components at the outlet of the catchment were identified and characterized: wastewater, surface runoff, PII, and RII. The model was applied and evaluated using monitored data from the Ecully catchment in France. The model demonstrated its suitability in replicating the observed hydrograph and estimating CSO volumes. Two sewer system scenarios were proposed, investigating the effect of partial and complete reduction of PII and RII on CSO volumes. The results showed a reduction of the annual CSO volume by 5 % to 7.5 %, and 12 % to 17 %, in the first and second scenario, respectively. To compare the performance of these scenarios with stormwater management strategies, two other scenarios were considered where source control measures allowed infiltration of the first 5 and 10 mm of rainfall. The results demonstrated that these measures could, respectively, reduce CSO volumes by 13 % to 48 % and completely eliminate CSO for half of the events. This study highlights the limitations of relying solely on PII and RII strategies to eliminate CSO events and emphasizes the necessity of considering stormwater management strategies.