Uncertainty analysis of a pollutant-hydrograph model in assessing inflow and infiltration of sanitary sewer systems

Abstract Rain-derived Inflow and rain-induced infiltration (RDI and RII) is a serious problem in urban drainage systems. Cost-effective and simplified RDI and RII estimation methods have been developed such as the conductivity-based method, nonetheless the parameter uncertainty had seldomly been analyzed. In this paper, an uncertainty analysis was proposed for a pollutant-hydrograph model developed for assessing RDII based on wastewater conductivity. The uncertainty and sensitivity of model parameters were analyzed using the Generalized Likelihood Uncertainty Estimation (GLUE) method. Different model scenarios including rainfall types, rainfall events, and different sewer systems were simulated in this model. The model results indicate the confidence of inflow and infiltration rate (RRDI, RRII) in residential area is much higher than that in the pump stations and WWTPs. The distribution disparity of RRDI and RRII also reflects the physical characteristic of the sewer network, which can be used to analyze sewer conditions such as pipe damages and misconnections. This novel conductivity-based method shows its improved performance compared to the traditional flow-based methods with supportive RDII data.