Enhancing near-shore water quality prediction with big data and AI
ID：1489
Oral (invited)
2025-01-16 08:45 （China Standard Time）
Session：Session 18-The River-Estuary-Bay Continuum: Unveiling the Carbon and Nitrogen Cycles Under Global Change
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