An empirical analysis of residential meter degradation in Gauteng Province, South Africa

  • Ryan Fourie Postgraduate School of Engineering Management, University of Johannesburg, Johannesburg, South Africa
  • Annlizé L Marnewick Postgraduate School of Engineering Management, University of Johannesburg, Johannesburg, South Africa
  • Nazeer Joseph Department of Applied Information Systems, School of Consumer Intelligence and Information Systems, University of Johannesburg, Johannesburg, South Africa
Keywords: water meter degradation, residential meters, apparent losses, meter replacement, empirical analysis

Abstract

Understanding the degradation rates of water meters assists utilities in making informed management decisions regarding meter replacement programmes and meter technology selection. This research evaluated the performance of 200 residential meters of two different technologies commonly used in Gauteng, South Africa, namely velocity meters and volumetric meters. This was done by conducting empirical meter testing in a verification laboratory and evaluating the degradation accuracy of each meter technology based on age and volume. Results indicate that velocity meters experience an accuracy degradation rate of approximately −1.13% per 1 000 kL of volume passed through the meter and an inferred initial error of −10.80%.  Meter accuracy was not strongly related to age of the velocity meters tested. Volumetric meters did not exhibit a strong link with either age or accumulated volume, indicated by a loose grouping of results. These results indicate that accumulated volume of a velocity meter is a more reliable predictor of accuracy than age, and should be used when planning replacement strategies for velocity meters. Additionally, the lack of predictable degradation rates related to either age or accumulated volume for volumetric meters indicates that the accuracy of volumetric meters is primarily affected by other external factors, such as particulates or entrained air in the water network.  These findings will assist utility managers in predicting the accuracy of their meter fleet and in making informed decisions regarding meter replacement.

Views
  • Abstract 51
  • PDF 20
Views and downloads are with effect from 11 January 2018
Published
2020-10-27
Section
Research paper