A stochastic sewer model to predict pipe flows and pollutant loads in an urban drainage system

Abstract

[EN] This work implemented a stochastic sewer model (SIMDEUM-WW) to forecast dry weather sewer flows and pollutant loading, from probabilistic household demand patterns based on information about inhabitants and appliance usage. The probabilistic outputs were fed into MIKE URBAN (DHI) for hydrodynamic and water quality simulations. The MIKE URBAN model consists of a 1D sewer network model. The model was validated against field measurement data and the results show that the SIMDEUM-WW can adequately calculate wastewater and pollutant loading. However, the SIMDEUM-WW was originally calibrated on households in the Netherlands such that errors were observed in the UK application. The uncertainties in actual flow and pollutant loading also contributed to the inaccuracy of modelling results.