A Survey on Recent Research Trends Towards Smart Water Grid System for Sustainable Urban Water Management and Leakage Localization.

Abstract: Rapid urbanization, increasing water demand, aging distribution infrastructure and climate variability have intensified the need for sustainable urban water management. Conventional water distribution systems rely heavily on inspection and reactive maintenance making it difficult to detect and localize small leaks before they become major failures. Smart Water Grid systems address this challenge by integrating Internet of Things sensors, smart meters, wireless communication, hydraulic modelling, cloud and edge computing, machine learning, graph-based learning and Digital Twin technologies. This literature review examines research on smart water distribution systems, with particular emphasis on leakage detection and localization. Recent studies show a transition from pressure- and flow-based approaches toward data-driven and hybrid physics-informed techniques. Three-dimensional convolutional neural networks, graph networks, machine-learning classifiers, wavelet-based signal processing, acoustic localization and mixture-of-experts architectures have demonstrated promising results. However reported studies remain dependent on simulated or laboratory data and performance can degrade when network topology, sensor availability, demand patterns or hydraulic-model assumptions change. The review identifies research gaps in real-world validation, sensor placement, uncertainty quantification, explainable AI, cybersecurity, interoperability and scalable edge implementation. Finally, a research framework is proposed for a Smart Water Grid combining distributed sensing, topology-aware AI, hydraulic constraints, real-time communication and Digital Twin-assisted decision support.

Keywords: Smart Water Grid, Smart Water Distribution Network, Sustainable Urban Water Management, Water Leakage Detection, Leakage Localization, Internet of Things Machine Learning, Graph Neural Networks, Digital Twin, Smart Metering.