AI and Big Data in Future Water Resources
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: closed (30 December 2022) | Viewed by 440
Special Issue Editors
Interests: artificial intelligence and water engineering applications; optimal allocation of urban water resources; disaster prevention and mitigation of urban waterlogging; optimal design and safe operation of urban water distribution networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The problem of water resources scarcity is still challenging due to human activities and climate change. Massive water infrastructures such as reservoir and inter-basin water transfer have been built to tackle the temporal-spatial differences of water resources across the world. However, understanding how to operate these complex systems using traditional approaches still represents a research gap. Innovations in information and communications technology (ICT) have advanced the resources issues to be solved. Monitoring, data analytics, and artificial intelligence are promising technologies in engineering planning, design, operation, and maintenance management. The innovative technologies could lower capital and operational costs, secure infrastructure operation, and mitigate greenhouse gas emission. Therefore, infrastructure sustainability and the efficient utilization of water resources can be realized in this field of study.
For this Special Issue we welcome papers on big data and AI applications to water supply systems, water transfer systems, reservoirs, etc. The scope is a cross/multi-discipline view of ICT and water engineering. The Special Issue proposed will provide valuable information to the readership of Water.
Prof. Dr. Haixing Liu
Prof. Dr. Aleksandr Tskhai
Guest Editors
Manuscript Submission Information
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Keywords
- water resources
- water supply systems
- water transfer
- artificial intelligence
- big data
- reservoir operation
- pump and valve operation
- machine learning
- time series data
- optimization
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