On the Potential of Smart Water Supply Grid in Semi-Arid Region

The concept of smart water supply grids has emerged as a promising response to the evolving challenges faced by traditional water supply systems. Traditional water supply systems are grappling with sustainability challenges such as increasing water main breaks, diminishing freshwater resources, untraceable non-revenue water usage, and escalating water demand. The condition worsens in arid- or semi-arid regions which also suffer from water scarcity due to harsh climate effects, surface water inaccessibility, water loss, and over-exploitation. Smart water infrastructure consists of online monitoring sensors and smart meters at the physical systems layer, various analytical tools, and visualization platform for optimal decision-making by the management authorities. The tighter integration of these components through IoT devices and advanced technologies including artificial intelligence and machine learning, tailored hybrid models for water networks hydraulics and water quality, is crucial in achieving digital twin for water management. This integration allows improved leakage reduction, pressure management, water quality protection, and overall system resilience. We present a case study of the development of a smart water supply system in the IIT Jodhpur campus situated in a semi-arid region of the state Rajasthan, India. We elucidate all phases of the study, i.e., sensor placement, data collection, mathematical modeling, and validation study analysis, addressing several challenges with real-time data and field deployment of digital twin technology. This study underscores the ongoing and incremental digital transition towards smart water systems, which is expected to yield significant benefits if collaboration among academia, industry, and government is effectively fostered. The present approach offers a robust framework for tackling water scarcity challenges in arid- or semi-arid regions and to create sustainable and resilient urban water infrastructures that are capable of adapting to both current and future challenges.