Modeling Dry Weather Wastewater Flow in Sewer Networks

Abstract

A model to predict the spatial and temporal variation of domestic dry weather flow in sewer networks was developed in this paper. A probabilistic framework was used to interpret intermittent appliance usage and methods for modeling the spatial distribution of inflow, and multiple appliances were developed. The concept of expected flow was introduced to overcome the problem of converting short-term, intermittent inputs into long-term, continuous baseflow suitable as an upstream boundary condition for a Muskingum-Cunge flow model. A small-scale domestic appliance usage survey was carried out to provide the necessary input data. The model was verified on a small combined sewer network in southeast England, using 25 days of dry weather flow data. The accuracy of mean daily and peak flows fell within ±10% of the measured values, and the overall fit of the data throughout the day was found to be good. The long-term variability of flow about its mean at any instant during the day was also successfully modeled.