Artificial Intelligence, Digital Twins and Intelligent Operation for Water Infrastructure

Dear Colleagues,

Water infrastructure—including dams, levees, reservoirs, canals, water supply systems, and irrigation networks—is facing increasing challenges arising from climate change, aging facilities, growing operational complexity, and rising demands for safety, resilience, and sustainability. Recent advances in artificial intelligence (AI), digital twin technologies, sensing systems, and intelligent operation provide unprecedented opportunities to transform the planning, monitoring, maintenance, and management of water infrastructure throughout its life cycle.

This Special Issue aims to present the latest research and technological developments in AI-driven and digital twin-enabled approaches for intelligent water infrastructure. Original research articles, review papers, and case studies are welcome. Topics of interest include, but are not limited to, artificial intelligence and machine learning, digital twins for water infrastructure, structural health monitoring, intelligent inspection and maintenance, remote sensing, reliability and probabilistic assessment, risk analysis and uncertainty quantification, predictive maintenance, resilience assessment, life-cycle management, data/mechanism driven modeling and simulation, robotics and autonomous inspection, decision support systems, climate adaptation and disaster risk reduction, economic assessment and policy decision-making for water infrastructure and water-related disasters, and smart operation and management of water infrastructure.

By bringing together innovative methodologies, supporting theories, and practical engineering applications, this Special Issue seeks to promote interdisciplinary collaboration and accelerate the development of intelligent, resilient, and sustainable water infrastructure. We warmly invite researchers and practitioners from academia, industry, and government agencies to contribute their latest findings and share their valuable experiences. 

Dr. Junru Li
Guest Editor

Dr. Haoran Huang
Guest Editor Assistant

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