According to an Environmental Protection Agency (EPA) report [1
]: “System rehabilitation is the application of infrastructure repair, renewal, and replacement technologies to return functionality to a drinking water distribution system or a wastewater collection system”. The process of intervention planning and prioritization is a function of a network’s current condition assessment, the extent of critical repair needs, the availability of funding for rehabilitation work options, and the ability to inspect and assess the condition and deterioration rate of each element [2
]. Asset management activity and life cycle analysis drive the broad activities that determine system-wide planning.
Among the possible alternatives for leakage reduction, asset replacement is quite expensive compared to active leakage control (ALC) and pressure management (PM). However, if the condition of the underground assets is so poor ALC and PM do not provide a sustainable solution. A well-managed water loss program should always include a budget for selective replacement of mains and/or service pipes specifically to reduce leakage if ALC, or PM is no longer a feasible option to mend the situation [3
]. Knowing when, where and how to rehabilitate pipes requires a good knowledge of the system performance, its conditions and the availability of decision support systems for rehabilitation planning. The present study describes a replacement planning approach based on mechanical reliability to minimize unsupplied water demand and pressure deficit.
Reliability Theory Applied to Water Distribution System
The definition of reliability is not unique, but depends on the specific field in which it is applied. Therefore, it is more precise to use this term in a general sense to indicate the overall ability of a system to perform its function [4
]. The mechanical and electrical complex systems are the main sectors where the theory of reliability found the initial application and only later was applied to hydraulic systems that exhibit some analogues aspects with those of the production, transport and distribution. Reliability is commonly defined, among other definitions, as “the probability of a device performing its purpose adequately for the period of time intended under the operating conditions encountered” [5
]. This comprises the concept of probability, adequate performance, time and operating conditions [6
For water distribution systems (WDSs), several types of reliability can be defined, in theory one for each set expected function of an asset or of the entire network [7
]. However, the literature has mainly focused on the concepts of mechanical and hydraulic reliability. The mechanical reliability can be defined as the probability that a component (new or repaired) experiences no structural failures during the time interval from time zero to time t
). The hydraulic reliability refers to the probability that a water distribution pipe can meet a required water flow level at a required pressure at each nodal demand [8
]. Walski [9
] observed that the topic of reliability is integrated to all parts of decision related to WDS design, operation and maintenance, even though most evaluations of reliability tend to focus on the design of the system. If the WDS has a sufficient redundancy to deliver water and is able to perform the expected function even for an aging infrastructure, it is therefore considered reliable. Moreover Kanakoudis et al. [10
] observed that reliability is the most common performance indicators used as maintenance priority criterion.
The reliability analysis could be used to identify repair works on existing system [12
] considering various random factors such as customer demand, mechanical failures, roughness indices, that could affect the performance or in the expansion of existing networks [13
] where the reliability is maximized with the support of computer models. Among the existing models to analyze the reliability of a water distribution system, “Management module” in WDNetXL (Version 4.0, IDEA RT, http://www.hydroinformatics.it
] is a tool that enables reliability analysis of the network by three specific functions: Reliability One Failure, Reliability Multiple Failure and Hydraulic Reliability. The first two functions analyze hydraulic behavior of a WDS by simulating single or multiple pipe or node failures/disconnections. Hydraulic Reliability function performs the analysis of the network hydraulic behavior by varying the boundary conditions such as pipe hydraulic resistances, background leakages, nodal customer demands, nodal free-orifice demands, and their combinations.
Reliability One-Failure function, which was used in this study, investigates all failure scenarios generated by disconnection of single pipe or node from the network. Given that a link may represent not only a pipe but also a device (valve or pump), a pipe failure can be associated also as a device failure. The reliability indicators proposed in this study are based on two parameters: unsupplied demand and pressure deficit. Both parameters are assessed from the failure events considered in Reliability One Failure function in a pressure driven, extended period simulation [16
] and are associated with Isolation Valve system (IVS) that disconnects the failing pipe or node from the rest of the network [17
]. Therefore, the study of WDS behavior resulting from failure events can be considered a mechanical reliability analysis.
The break rate λ that represents the number of break per kilometer per year is a common parameter associated with the mechanical reliability analysis [19
]. It is dependent on many factors such as installation year, pipe corrosion, diameter, break type, pipe material, seasonal variation, soil environment, break history, pressure, land use and pipe length. Consequently, to consider these factors individually to obtain a prevision of the expected break rate is a rather difficult task. Break rate is case specific and, therefore, it is advisable to calculate it at a cohort level through an analysis of the historical break data related to the specific network. Otherwise, it is also possible to use formulae taken from the literature from a similar case study. The break rate is assessed for different pipe cohorts defined by similar characteristics and grouped to have a representative statistical sample. Afterwards, the specific number of breaks per year is evaluated for each pipe by multiplying λ with the individual pipe length.