Abstract

Abstract Water loss in water distribution systems is one of the major problems faced by water utilities. The components of water losses should be accurately assessed and their priority should be determined. Generally, water balance analysis is used to quantify different components of water losses and identify the main contributor to high leakage rates. The leak flow rate is assumed to be static within a given calculation period during the calculation of real losses. Errors will inevitably arise during this process. This is mainly due to our limited understanding of a leak's growth process. To overcome this problem, the current work proposes the use of growth functions to represent a leak's growth process and establish a functional relationship between the leak flow rate and the leak duration. A leakage development model is adopted to simulate a leak's growth process and optimize the parameters of growth functions. The results show that the Richards function performs better than other growth functions and its mean absolute percentage error is 15.33%. Furthermore, the growth function could be used to calculate real losses and has the prospect of evaluating the effects of leakage detection.

Highlights

  • Over the past few decades, the shortage of water resources has gradually received attention

  • Four indicators are used to evaluate the performance of leakage development models (Bennett et al ): mean absolute error (MAE), mean absolute percentage error (MAPE), relative entropy (RE), and Nash–Sutcliffe model efficiency (NSE)

  • The results show that the Richards function performs better than the Logistic and Gompertz functions

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Summary

INTRODUCTION

Over the past few decades, the shortage of water resources has gradually received attention. Background or unreported leakages have small leak flow rates, they can cause significant water losses due to their long leak duration (Aboelnga et al ). A leak could exist for several detection periods until it is discovered, and its leak flow rate might vary over time (2) A leakage development model is adopted to simulate a leak’s growth process, and a method to calculate real losses using growth functions is proposed. This helps provide a new method for accurately quantifying each component of real losses (i.e., unreported losses or reported losses). The ‘Conclusions’ section summarizes this work and offers suggestions for future work

METHODOLOGY
21 Dec 2016 DN400 cast iron
RESULTS AND DISCUSSION
Method
CONCLUSIONS
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