The current water stress in some parts of the UK and the droughts experienced in the recent past exposing the vulnerability of some UK companies in maintaining supplies have been major drivers for more efficient use of water. Leakage control is thus seen as a major demand management strategy to offset the supply and demand imbalances and Water companies are working hard to reduce leakage further to economic levels. However, in an attempt to control leakage, a number of concerns arise which need to be addressed for a more sustainable solution to the problem of leakage.
The research carried out in the past to address the problem of leakage has been mostly focussed on the development of decision support systems based on statistical and deterministic models for systematic and economical replacement of deteriorating pipes, with minimal work on methodologies for real-time identification of damage or leakage in the pipe network. However, such models do not cover the whole range of the problem of leakage; they can only predict the time to failure with limited accuracy, with no ability to predict incidental failure which is bound to occur in any water supply system.
This research was therefore aimed at assessing the current leakage management approaches employed within the UK and identifying possible areas of improvement for more sustainable leakage management. In addition, the research aimed at developing a simple fuzzy-logic-based methodology for real-time identification of burst incidences from flow data for purposes of earlier identification and minimisation of interruption to supply and the resulting inconveniences to the customer.
A review of the current leakage management approaches in the UK revealed a number of concerns which needed to be addressed for more sustainable leakage control. These included the formulation of holistic policies to optimise leakage control; a balance between leakage reduction by pressure reduction and the energy requirements to boost supply; inclusion of environmental and social costs in the calculation of the ELL; metering of water for more accurate estimation of leakage; and the use of performance indicators for water loss which can give an indication of progress towards sustainability, among others. This demonstrated a need for a more holistic approach to leakage management for a more sustainable solution to leakage.
The fuzzy logic-based methodology developed for burst identification was based on the normal range of flow values under normal conditions. The deviation from normal flow was either classified as a ‘leak’ or ‘possible leak’ depending on the degree of deviation. The Fuzzy Inference System (FIS) designed identified burst incidences to a good extent but failed to identify burst incidences in real-time, occurring at periods of minimum demand. This problem however could be solved by use of a composite FIS. The methodology developed is simple and offers flexibility in the ability to be combined with other soft computing methods to attain more robust results; a high tolerance for noise inherent in flow and pressure data; and allows for incorporation of human knowledge of the system in the design of the FIS.
The final outcome of this research is a set of recommendations for more sustainable management of leakage in the UK and a fuzzy-logic–based methodology for identification of burst incidences. If developed further, the method has a potential for use as a powerful tool for identification of burst incidences from real-time flow data. This is expected to lead to the transformation of the water industry, by enabling the industry to attain a new level of service with minimal interruption to supply and inconveniences to the customer.