Presentation Details
Enhancing near-shore water quality prediction with big data and AI
ID：1489
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Updated Time：2024-12-31 21:28:29
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Oral (invited)
Start Time：2025-01-16 08:45（Asia/Shanghai）
Duration：15min
Session：S18 Session 18-The River-Estuary-Bay Continuum: Unveiling the Carbon and Nitrogen Cycles Under Global Change »
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Abstract
Near-shore water quality is influenced by complex terrestrial and oceanic interactions, making accurate prediction challenging. This presentation explores how big data and machine learning enhance water quality predictions in human-impacted bays. Key cases include pollutant flux estimation from unmonitored watersheds, nowcasting with in-situ monitoring, and spatiotemporal reconstruction of multi-source data. Future research directions will also be discussed.
Keywords
big data, AI, machine learning, water quality, bay, near-shore, model
Speaker
Yi Zheng
Professor Southern University of Science and TechnologySubmission Author
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Important Date
-
Conference Date
Jan 13
2025
toJan 17
2025
-
Sep 27 2024
Draft paper submission deadline
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Feb 17 2025
Registration deadline
Sponsored By
State Key Laboratory of Marine Environmental Science, Xiamen University
Organized By
State Key Laboratory of Marine Environmental Science, Xiamen University
Department of Earth Sciences, National Natural Science Foundation of China
Department of Earth Sciences, National Natural Science Foundation of China
Contact Information
- Kejing GU
- xm******@xmu.edu.cn
- +86*********
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