Optimizing Non-Revenue Water Management: A Review

Abstract

Non Revenue Water (NRW) refers to the volume of water that is distributed from the water plant but does not get billed to customers, which is a major challenge for water bodies.It represents the difference between the total volume of water pumped into the water distribution system (WDS) and the volume actually billed to customers.NRW is composed of three components: physical losses, commercial losses, and unbilled authorized consumption.These losses cause financial deficits, increased operational costs, and infrastructure deterioration, making NRW reduction a critical challenge for water bodies globally. This study reviews optimization strategies for minimizing NRW, focusing on advanced metering infrastructure (AMI), remote leak detection (acoustic, pressure, and flow sensors), Geographic information systems (GIS), data analytics, machine learning, and digital twin modeling. Findings suggest that integrating emerging technologies, predictive analytics, and data-driven decision-making can significantly enhance water distribution efficiency. Future research should focus on AI-driven optimization, predictive maintenance, and sustainable water management strategies to optimize non revenue water