Source Contamination Detection and Identification of Affected Spots in the Intermittent Water Supply System Using Mixed Tool-Based and Data-Driven Machine Learning Techniques

Abstract

AbstractIt has always been difficult to model the real-life intermittent water distribution system. This can be achieved by adopting operational setups of the modeling tool. The Gajrawadi water supply network of Vadodara City, India, serves as the case ...Practical ApplicationsThe present study provides a framework for machine learning (ML) applications to detect the source contamination and affected area in intermittent water distribution system (IWDS). EPANET was used to simulate pressures, actual demand,...