Advanced control is getting increasingly demanded in water and wastewater treatment systems. Various case studies have shown significant savings in operating costs, including energy costs, and remarkably short payback times. It has been demonstrated that instrumentation, control and automation (ICA) may increase the capacity of biological nutrient removing wastewater treatment plants by 10-30 % today. With further understanding and exploitation of the mechanisms involved in biological nutrient removal the improvements due to ICA may reach another 20-50% of the total system investments within the next 10-20 years. Disturbances are the reason for control of any system. In a wastewater treatment system they are mostly related to the load variations, but many disturbances are created also within the plant. In water supply systems some of the major disturbances are related the customer demand as well as to leakages or bursts in the pipelines or the distribution networks. Hardly any system operates in steady state but is more or less in a transient state all the time. Water and energy are closely related. The role of energy in water and wastewater operations is discussed. With increasing energy costs and the threatening climate changes this issue will grow in importance.

ABSTRACT In this paper, we present an overview of the continuous monitoring system we are developing for the water distribution system in Singapore. We discuss the framework and techniques that enable real-time detection of pipe burst events.

In this paper we present techniques for detecting and locating transient pipe burst events in water distribution systems. The proposed method uses multiscale wavelet analysis of high rate pressure data recorded to detect transient events. Both wavelet coefficients and Lipschitz exponents provide additional information about the nature of the signal feature detected and can be used for feature classification. A local search method is proposed to estimate accurately the arrival time of the pressure transient associated with a pipe burst event. We also propose a graph-based localization algorithm which uses the arrival times of the pressure transient at different measurement points within the water distribution system to determine the actual location (or source) of the pipe burst. The detection and localization performance of these algorithms is validated through leak-off experiments performed on the

Selection and peer-review under responsibility of the CCWI2013 Committee

An algorithm which compares measured and predicted water demands to detect pipe bursts was developed and tested on three data sets of water demand and reported pipe bursts of three years. The algorithm proved to be able to detect bursts where the water loss exceeds 30 % of the average water demand in the area. The accuracy depends on the acceptable number of false alarms By simultaneously running the algorithm in adjacent supply areas, and combining the monitoring results the number of false alarms could be reduced.