Effect of rainfall-derived inflow and infiltration on dissolved organic matter in urban sanitary sewers using chemometric and machine learning approaches

Abstract

This study investigated changes in dissolved organic matter (DOM) properties within urban sanitary sewers influenced by groundwater infiltration and excessive rainfall-derived inflow and infiltration (RDII). It employed optical indices and fluorescence excitation-emission matrix-parallel factor analysis (PARAFAC) coupled with self-organizing map (SOM) to compare DOM characteristics during wet weather flows (WWFs) and dry-weather flows (DWFs). Sampling sites impacted by RDII were identified based on flowrate. Optical indices and PARAFAC components (C1–C4) were used to differentiate DOM properties between DWFs and WWFs. In WWFs, E₂/E₃ and S_350-400 increased, while spectral ratio (S_R) decreased, indicating a shift towards smaller organic matters. Reduced fluorescence and humidification indices suggested the input of fresher/terrestrial organic matters. C3 and C4 exhibited significant distinctions, showing increased C3 and decreased C4 levels. The PARAFAC-SOM modeling further illustrated that water samples in the urban sewer system could be categorized based on the dominance of DOM properties. Principal component analysis revealed separation between DWF and WWF samples in principal component 1 (PC1), associated with molecular size. PC2 was linked to microbial activity in WWFs. Notably, DWF samples from the NY-11 site shifted to the positive side of the PC1 axis, while their corresponding WWF samples moved to the negative side.