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Water utilities in developing countries are struggling to provide customers with a reliable level of service due to their peculiar water distribution characteristics including poorly zoned networks with irregular supply operating under restricted budgets. These unique conditions demand unique tools and methods for water loss control. Water loss management: Tools and Methods for Developing Countries provide a decision support toolbox (appropriate tools and methodologies) for assessing, quantifying, prioritising strategies and improving water distribution efficiency in the developing countries. It promotes good stewardship of water resources and sustainable delivery of water supply services in urban water distribution systems.

The study presented in this manuscript investigates the patterns that describe reliability of water distribution networks focusing to the node connectivity, energy balance, and economics of construction, operation and maintenance. A number of measures to evaluate the network resilience has been developed and assessed to arrive at more accurate diagnostics of regular and irregular demand scenarios. These measures have been proposed as a part of the methodology for snap-shot assessment of network reliability based on its configuration and hydraulic performance. Practical outcome of the research is the decision support tool for reliability-based design of water distribution networks. This computer package named NEDRA (NEtwork Design and Reliability Assessment) consists of the modules for network generation, filtering, initialisation, optimisation, diagnostics and cost calculation, which can be used for sensitivity analyses of single network layout or assessments of multiple layouts. The study concludes that none of the analysed aspects develops clear singular patterns. Nevertheless, the proposed network buffer index (NBI) and the hydraulic reliability diagram (HRD) as visual representation of the network resilience give sufficient snap-shot pointing the composition of the index value, and displaying possible weak points in the network that can be hidden behind the averaged values of various reliability measures.