FIELD VALIDATION OF 'OPTIMAL' INSTRUMENTATION METHODOLOGY FOR BURST/LEAK DETECTION AND LOCATION

Leakage is a commonly accepted feature of Water Distribution Systems (WDS). The UK claims to be at, or close to, an Economic Level of Leakage (ELL), where the value of water lost is marginal to the cost of finding and fixing leaks. However ELL is not necessarily fixed. Drivers such as energy, carbon and climate change are forcing re-evaluation of the economics and sustainability drivers are requiring inclusion of social (public acceptance, levels of service) and environmental (natural resources) ‘costs’. Hence there is a need for water companies to improve their awareness and location of bursts/leaks as they occur. This paper presents a methodology to determine, and the results of fieldwork to validate, the ‘optimal’ placement of pressure instruments within Distribution Management Areas /District Meter Areas (DMAs) to detect and locate new leak/burst events. While flow data is generally regarded as a superior indicator of leak/burst events, pressure instruments have the advantage of lower cost and ease of deployment. Hence it is feasible to justify the deployment of additional pressure instrumentation to improve leak/burst detection and location. However the placement of instrumentation remains a challenge. The methodology presented here is based upon complete enumeration studies using hydraulic model simulations of multiple leak/burst events and then evaluating the responses at all potential instrumentation points. This produces a sensitivity matrix of all possible instrument locations to all possible leak/burst events. The matrix can then be searched for combinations of instruments that provide sensitivities to different regions (discrete or selectively overlapping) to enable detection and location of new events. Results of extensive fieldwork are presented to validate the proposed modeling methodology. This fieldwork utilized fire hydrant opening and flushing to simulate the additional system flow of leak/burst events. Data presented confirms the ability of the approach to predict the instrument sensitivities across numerous points within a selected DMA, as well as the ability to provide location information. Results are from current UK industry standard data sampling and hydraulic models confirming the practicality of the method.