Estimating sanitary sewer pipeline infrastructure from basic characteristics of a service zone

Abstract

The standard design and cost estimation for a sewer network involves considerable time and financial investment. There are, however, many cases  where a rapid assessment of the sewer infrastructure or related costs associated with a service zone might be required. Although there are  numerous approaches to rapid sewer infrastructure estimation in the literature, to date, no widely available tool has been developed that can be  applied to reliably estimate the expected sewer pipeline infrastructure associated with a service zone in South Africa. The aim of this study was to  develop a method for estimating the sewer pipeline infrastructure required for a service zone, based on limited information, that could be applied  to future developments. A database of South African sewer network data was used in the development of three major study outcomes. Study  Outcome I involved developing regression models for estimating the total sewer pipeline length using only basic service zone characteristics.  Models were developed for different categories of land use and area size, allowing for estimation of the total pipeline length as a function of the  service zone area size, relief, and the density of contributing users. Study Outcome II involved determining the average pipeline diameter  distributions for different types of service zones, enabling disaggregation of the total pipeline length into lengths per diameter. Study Outcome III  involved determining the average number of manholes per kilometre of sewer pipeline. Combined, the three study outcomes form an infrastructure  estimation tool that enables the sewer pipeline length per approximate diameter and the number of manholes associated with a  service zone to be estimated, applicable to service zones smaller than 450 hectares. This study illustrates how the same methodology can be  followed to develop similar tools which are applicable to other specific regions or development types, provided an appropriate dataset is obtainable.