A prioritization method for replacement of water mains using rank aggregation

Risk management in water supply networks: Aveiro case study

Water supply networks are critical infrastructures essentials to health, safety, economic and social well-being which have to be maintained and preserved to ensure their proper functioning. Considering the importance of these critical infrastructures, the risks to which they are exposed and the consequences of such risks must be analysed. Thus, it is important that companies responsible for the management of these assets incorporate risk management in their activities. In the scope of risk management, this paper intends to identify the vulnerabilities of water supply infrastructures, by analysing the risks they are exposed and identifying the measures that need to be implemented or reinforced. Risk assessment methodologies were analysed to identify the advantages and disadvantages of each one. As a case study, the water supply network of the Aveiro municipality in mainland Portugal was used. This network was analysed resourcing ArcMap, ArcGIS desktop software, which allows a better understanding of the water supply network. Risk management was applied and the probability and possible consequences of six distinct categories of threats were determined in eight scenarios, allowing the development of risk maps concluding that all these scenarios are in a low or medium level of risk. To decrease the vulnerability of the water network, a set of plans and specific measures have to be developed.

An Efficient Burst Detection and Isolation Monitoring System for Water Distribution Networks Using Multivariate Statistical Techniques

Detection and isolation of burst locations in water distribution networks (WDN) are challenging problems in urban management because burst events cause considerable economic, social, and environmental losses. In the present study, a novel monitoring and sensor placement approach is proposed for rapid and robust burst detection. Accordingly, a hybrid principal component analysis (PCA) and standardized exponential weighted moving average (EWMA) system is proposed for WDN monitoring and management. In addition, the optimal sensor configuration is obtained using PCA, k-means clustering, and a sensitivity analysis considering the diurnal patterns and the noises of pressure and flowrate data in the WDN. The proposed system is applied to a branched WDN, and the results are compared to those obtained with conventional monitoring systems. The results show that the proposed system detected the burst occurrence regardless of noise size with a detection rate of 93%. Compared to conventional systems, the isolation ratio improved by 10%, indicating that the bursts were isolated more accurately. In addition, the corresponding sensor configuration was 40% less expensive than the conventional systems.