Sewer asset management gained momentum and importance in recent years due to economic considerations, since infrastructure maintenance and rehabilitation directly represent major investments. Because physical urban water infrastructure has life expectancies of up to 100 years or more, contemporary urban drainage systems are strongly influenced by historical decisions and implementations. The current decisions taken in sewer asset management will, therefore, have a long-lasting impact on the functionality and quality of future services provided by these networks. These decisions can be supported by different approaches ranging from various inspection techniques, deterioration models to assess the probability of failure or the technical service life, to sophisticated decision support systems crossing boundaries to other urban infrastructure. This paper presents the state of the art in sewer asset management in its manifold facets spanning a wide field of research and highlights existing research gaps while giving an outlook on future developments and research areas.
The occurrence of pipe failures in water networks cause major technical, economic and socio-economic impacts. Thus, comprehensible and reliable failure prediction models are required for operational and strategic planning purposes in order to guarantee a sustainable water network development. A lot of research work has been done in this field and the developed failure prediction models can be applied under various circumstances. However, most of the existing models have two major limitations: they consider a static state of the network without taking future developments into account, and they can hardly be applied to networks where only limited data on single pipe level is available. This paper describes a failure prediction model on the network and pipe type level, which is integrated in the KANEW framework for strategic rehabilitation planning. First testing results with this approach are promising.
This paper aims to enable the relevant use of water main service lifetime and failure data to build a medium or long term infrastructure management plan. Firstly, how to estimate the service lifetime distribution of water mains using observations of decommissioning times which are possibly left-truncated and predominantly right-censored, is shown. Three methods are presented: a non-parametric method another based on the parametric Weibull distribution, and a third based on the parametric Herz distribution. An application with actual data related to grey cast iron water mains of two large French and German water distribution networks illustrates the implementation of the theoretical methods. The paper then investigates the link between failure rate and pipe renewal, and discusses the use of observation-based service time survival functions for infrastructure asset management.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.