Digital Twin in Water Resources: Opportunities, Challenges, and Future Trends

The escalating water crisis in Iran, especially in arid and semi-arid regions, necessitates a fundamental revision of traditional water management approaches. Declining precipitation, disproportionate demand growth, and underdeveloped data infrastructures challenge current decision-making systems. In this context, Digital Twin technology offers transformative capabilities such as real-time monitoring, scenario simulation, and proactive water resource management decision-making. This paper reviews global experiences and analyzes the Iranian context to propose a localized framework for implementing Digital Twins in national water systems. The framework comprises five integrated and adaptable components: data convergence, situational intelligence, communicative regulation, human–machine interaction, and reflexive decision-making. Alongside the introduction of complementary technologies like Internet of Things, remote sensing, and Artificial Intelligence, the study explores the practical challenges and opportunities of deploying this innovation in Iran and provides strategic pathways toward smart water governance. The framework serves as a conceptual and practical step toward transitioning from reactive management to data-driven, flexible, and sustainable water governance.

Keywords:

Digital Twin , Water Resources Management , Smart Governance , Remote Sensing , Real-Time Analysis