Advances and Major Achievements in China’s Digital Twin River Basin Development
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 18
Special Issue Editors
Interests: digital twin watershed; machine learning; big data; flood control; knowledge graph; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: digital twin watershed; urban flooding; emergency decision-making; flood control; remote sensing; geographic information system; artificial intelligence
Interests: remote sensing; GIS; water cycle; hydrological model; precipitation extremes; floods; droughts; spatial analysis; land use and land cover change
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Since 2021 (China's 14th Five-Year Plan period), China has launched the construction of digital twin water conservancy systems to achieve smart management goals. Currently, annual investment in digital twin water conservancy exceeds CNY 10 billion and continues to grow. Water conservancy management departments across the country have significantly enhanced the intelligence of operations such as flood control, water resource management, and project scheduling through developing digital twin river basins, digital twin water networks, and digital twin engineering projects. Technologies such as machine learning, knowledge graphs, large language model, remote sensing, drones, high-performance computing, and virtual simulation have been deeply integrated. This has led to the development of software products including remote sensing monitoring platforms, knowledge platforms, data foundation management platforms, digital twin platforms, and integrated decision support platforms for flood control projects. This Special Issue is dedicated to showcasing China's exemplary cases and experiences in digital twin water resources management. Submissions are encouraged to cover the following aspects: case (technology) background, technical framework, application targets, achieved outcomes, and areas for improvement.
Prof. Dr. Yesen Liu
Dr. Yueqin Zhu
Dr. Yaohuan Huang
Guest Editors
Manuscript Submission Information
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Keywords
- China
- digital twin hydrology
- knowledge graph
- large language model
- virtual simulation
- satellite remote sensing
- flood control
- water resources
- water network
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