This paper presents a critical review of the transformative potential of integrating digital twins and artificial intelligence (AI) in modern water resource management, addressing escalating challenges of water scarcity, pollution, and climate-driven disruptions. Traditional water management systems often fall short of providing the timely insights needed to handle increasingly complex water quality and distribution issues. Digital twins, enhanced by AI, offer an innovative solution by creating real-time, dynamic simulations of water systems that enable continuous monitoring, predictive maintenance, and proactive risk management. Through in-depth analysis of global case studies including AI-driven water quality prediction in Malaysia, urban water distribution and energy consumption optimization in Singapore, wastewater management advancements in Europe, improvements in wastewater treatment plants, and efforts to address inefficiencies in the outdated water system in China, this study highlights substantial improvements in predictive accuracy, resource efficiency, and environmental resilience achieved by these technologies. AI integration within digital twins empowers operators to anticipate and respond to water quality fluctuations, infrastructure stress points, and pollution events, ensuring regulatory compliance and sustainable water use. Despite their proven benefits, the paper also discusses significant implementation barriers, including data integration challenges, high infrastructure costs, and cybersecurity concerns. This research underscores digital twins and AI as pivotal tools for advancing sustainable water management globally, advocating for further innovation to scale these technologies to underserved regions. Together, digital twins and AI hold immense promise in building resilient, adaptive water systems capable of meeting future environmental and urban demands.

Digital Twins, Artificial Intelligence (AI), Water Resource Management, Predictive Analytics, Real-Time Monitoring, Environmental Sustainability