Over the last three decades, the increasing development of smart water meter trials and the
rise of demand management has fostered the collection of water demand data at …

This paper presents a completely data-driven and machine-learning-based approach, in two
stages, to first characterize and then forecast hourly water demand in the short term with …

Smart meters installed at the user-level provide a new data source for managing water
infrastructure. This research explores the use of machine learning methods, including …

The commonly used Poisson rectangular pulse (PRP) model, employed for simulating high-
resolution residential water consumption patterns (RWCPs), relies on calibration via medium …

One of the main parts of urban water consumption is residential water use. In this paper, a
new framework based on agent-based modeling is introduced to simulate the behavioral …

In the design of a water supply network, the use of traditional formulas of the peak factor may
lead to over-dimensioning the network pipelines, especially in small towns. This discrepancy …

Peak water demand is one of the most stringent operative conditions for a Water Distribution
System (WDS), not only for the intensity of the event itself, but also for its recurring nature …

Residential water demand consists one of the most uncertain factors posing extra difficulties
in the efficient planning and management of urban water systems. Currently, high resolution …

Water network partitioning (WNP) into District Meter Areas allows improving pressure
management, water budget, leaks detection, compared to classical redundantly looped …

Uncertainty-aware design and management of urban water systems lies on the generation
of synthetic series that should precisely reproduce the distributional and dependence …