The need for sustainable water infrastructure systems continues to grow as clean water is
essential for daily life. Despite efforts to sustain water distribution networks (WDNs), they …

To reduce leakage and improve service levels, water companies are increasingly using
statistical models of pipe failure using infrastructure, weather and environmental data …

Among the most widely predicted and accepted consequences of global climate change are
increases in both the frequency and severity of a variety of extreme weather events. Such …

The reliability of the water distribution system is critical to maintaining a secure supply for the
population, industry and agriculture, so there is a need for proactive maintenance to help …

Predicting pipe failures using statistical modelling benefits from detailed knowledge of the
conditions and circumstances which influence such failures. Incorporating this knowledge …

Watermains are both directly and indirectly affected by climatic conditions such as
temperature and precipitation. Research has been conducted to understand and model the …

Several statistical models have been proposed to study effects of different covariates in the
failure of water pipes. In this paper, three statistical models, the Weibull proportional hazard …

This paper presents a novel decision support framework for water utilities to automatically
create yearly pipeline rehabilitation plans while considering multiple parameters, including …

This paper examines the impact of weather conditions on pipe failure in water distribution
networks using artificial neural network (ANN) and evolutionary polynomial regression …

Urban water distribution systems are critical infrastructures, and their failure can lead to
significant economic, environmental, and social losses including flood streets and loss of …